Professor David Banjerdpongchai, Ph.D.
ศ. ดร.เดวิด บรรเจิดพงศ์ชัย
Education
- Ph.D. Electrical Engineering 1997 Stanford University, USA
- M.S. Electrical Engineering 1992 Stanford University, USA
- Bachelor of Engineering (First class honor) 1989 Chulalongkorn University, Thailand
Email: David.B@chula.ac.th
Research Interest
- Industrial Automation
- Advanced process control
- Convex optimization
- Robust control design
- Control Application to Flexible Robot Arm
- Distillation Column
- Boiler
- HVAC System; Energy management system
- Energy Efficiency
- Load and RE Forecast
Research Cluster
Link to
1.
Haq, E U; Jianjun, H; Li, K; Ahmad, F; Banjerdpongchai, D; Zhang, T
In: Electrical Engineering, vol. 103, no. 2, pp. 953-963, 2021, ISSN: 09487921, (cited By 1).
@article{Haq2021,
title = {Improved performance of detection and classification of 3-phase transmission line faults based on discrete wavelet transform and double-channel extreme learning machine},
author = {E U Haq and H Jianjun and K Li and F Ahmad and D Banjerdpongchai and T Zhang},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85095603422&doi=10.1007%2fs00202-020-01133-0&partnerID=40&md5=88adad8a5c7e1f7e5c7f4a36821c9303},
doi = {10.1007/s00202-020-01133-0},
issn = {09487921},
year = {2021},
date = {2021-01-01},
journal = {Electrical Engineering},
volume = {103},
number = {2},
pages = {953-963},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Power transmission lines are the key network that transmits energy from the generation side to load. The complexity and uncertainty in the power system increase continuously due to the evolution of the smart grid, which needs an effective and accurate protection system. The faults in transmission lines affect the whole power system and also the consumers’ side. Therefore, accurate and precise identification of faults in transmission lines minimizes the losses and maximizes the functionality and reliability of the power network. Due to the recent advances in digital technology, an online scheme is used to locate the fault in transmission lines. In this paper, machine learning-based discrete wavelet transform and double-channel extreme learning machine method are proposed to locate and classify the faults in transmission lines. Db4 wavelet is used as a mother wavelet in the discrete wavelet transform for feature extraction up to nine levels. The proposed method validated on real-time data which achieves higher classification accuracies and less fault detection time. Results show that high-impedance non-linear faults have no effect on the proposed technique. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.},
note = {cited By 1},
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pubstate = {published},
tppubtype = {article}
}
Power transmission lines are the key network that transmits energy from the generation side to load. The complexity and uncertainty in the power system increase continuously due to the evolution of the smart grid, which needs an effective and accurate protection system. The faults in transmission lines affect the whole power system and also the consumers’ side. Therefore, accurate and precise identification of faults in transmission lines minimizes the losses and maximizes the functionality and reliability of the power network. Due to the recent advances in digital technology, an online scheme is used to locate the fault in transmission lines. In this paper, machine learning-based discrete wavelet transform and double-channel extreme learning machine method are proposed to locate and classify the faults in transmission lines. Db4 wavelet is used as a mother wavelet in the discrete wavelet transform for feature extraction up to nine levels. The proposed method validated on real-time data which achieves higher classification accuracies and less fault detection time. Results show that high-impedance non-linear faults have no effect on the proposed technique. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
2.
Anuntasethakul, C; Banjerdpongchai, D
Design of Supervisory Model Predictive Control for Building HVAC System with Consideration of Peak-Load Shaving and Thermal Comfort Journal Article
In: IEEE Access, vol. 9, pp. 41066-41081, 2021, ISSN: 21693536, (cited By 0).
@article{Anuntasethakul2021,
title = {Design of Supervisory Model Predictive Control for Building HVAC System with Consideration of Peak-Load Shaving and Thermal Comfort},
author = {C Anuntasethakul and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102626113&doi=10.1109%2fACCESS.2021.3065083&partnerID=40&md5=6654ce42869b04c7850ee6737c3bdf43},
doi = {10.1109/ACCESS.2021.3065083},
issn = {21693536},
year = {2021},
date = {2021-01-01},
journal = {IEEE Access},
volume = {9},
pages = {41066-41081},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {This paper proposes a design of a supervisory model predictive controller for a heating-ventilation-air-conditioning (HVAC) control system. The control objective is to minimize the operating cost and take into account of electrical load shaving and thermal comfort of users. To ensure that thermal comfort is well regulated, we utilize the Predicted Mean Vote (PMV) as an indicator and determine an acceptable bound of a desired set-point temperature. The control design consists of two layers, namely, a supervisory control (SC) layer and a model predictive control (MPC) layer. For the SC layer, we explore a configuration for the SC layer including the choice of predesign controller, the analysis of steady-state response, and the analysis of the possible range of the set-point temperature. We incorporate the effect of set-point temperature, air velocity, outside air temperature, heat load inside zone onto the HVAC electrical power. Then, we search for an optimal profile of the set-point temperature that minimizes a weighted sum of a total operating cost (TOC) and a thermal comfort cost (TCC). Moreover, exploration of trade-off between TOC and TCC helps us to achieve both control objectives efficiently. For the MPC layer, we formulate the control design with the objective of tracking the optimal set-point temperature and minimizing the control inputs. We apply the proposed control design to a complex dynamical model of HVAC system with volumetric flow rate, electrical power of heat exchanger, and removed moisture as control variables. When the allowable PMV of the zone is specified within 0.5, the TOC of the proposed supervisory MPC is reduced by 12.46% compared with that of the nominal operation. The maximum electricity demand of HVAC system is reduced by 13.43% and the electrical power profile is smoothly shaved under the proposed control scheme. Furthermore, the zone relative humidity is well regulated which corresponds to the assumption in the supervisory control. © 2013 IEEE.},
note = {cited By 0},
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pubstate = {published},
tppubtype = {article}
}
This paper proposes a design of a supervisory model predictive controller for a heating-ventilation-air-conditioning (HVAC) control system. The control objective is to minimize the operating cost and take into account of electrical load shaving and thermal comfort of users. To ensure that thermal comfort is well regulated, we utilize the Predicted Mean Vote (PMV) as an indicator and determine an acceptable bound of a desired set-point temperature. The control design consists of two layers, namely, a supervisory control (SC) layer and a model predictive control (MPC) layer. For the SC layer, we explore a configuration for the SC layer including the choice of predesign controller, the analysis of steady-state response, and the analysis of the possible range of the set-point temperature. We incorporate the effect of set-point temperature, air velocity, outside air temperature, heat load inside zone onto the HVAC electrical power. Then, we search for an optimal profile of the set-point temperature that minimizes a weighted sum of a total operating cost (TOC) and a thermal comfort cost (TCC). Moreover, exploration of trade-off between TOC and TCC helps us to achieve both control objectives efficiently. For the MPC layer, we formulate the control design with the objective of tracking the optimal set-point temperature and minimizing the control inputs. We apply the proposed control design to a complex dynamical model of HVAC system with volumetric flow rate, electrical power of heat exchanger, and removed moisture as control variables. When the allowable PMV of the zone is specified within 0.5, the TOC of the proposed supervisory MPC is reduced by 12.46% compared with that of the nominal operation. The maximum electricity demand of HVAC system is reduced by 13.43% and the electrical power profile is smoothly shaved under the proposed control scheme. Furthermore, the zone relative humidity is well regulated which corresponds to the assumption in the supervisory control. © 2013 IEEE.
3.
Jennawasin, T; Banjerdpongchai, D
Iterative LMI approach to robust static output feedback control of uncertain polynomial systems with bounded actuators Journal Article
In: Automatica, vol. 123, 2021, ISSN: 00051098, (cited By 0).
@article{Jennawasin2021,
title = {Iterative LMI approach to robust static output feedback control of uncertain polynomial systems with bounded actuators},
author = {T Jennawasin and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092714986&doi=10.1016%2fj.automatica.2020.109292&partnerID=40&md5=5e3df90e88bb1bf92d9724ec2ddb9b26},
doi = {10.1016/j.automatica.2020.109292},
issn = {00051098},
year = {2021},
date = {2021-01-01},
journal = {Automatica},
volume = {123},
publisher = {Elsevier Ltd},
abstract = {This paper presents a novel static output feedback stabilization of polynomial systems with bounded actuators. We propose a new sufficient condition for static output feedback design for nominal polynomial systems with constraints on input magnitudes. In the proposed stabilization condition, the system matrices and the Lyapunov matrices are separated, and hence parameterization of the controller is independent of the Lyapunov matrices. The main result is the novel parameter-dependent Lyapunov functions that are readily applied to robust static output feedback design of polynomial systems subject to parametric uncertainty. The proposed design conditions are bilinear in the decision variables. Hence, we provide iterative algorithms to solve the design problems. At each iteration, the design condition is cast as parameter-dependent linear matrix inequalities using the sum-of-squares technique and can be efficiently solved. The proposed approach leads to enhanced static output feedback design with computationally tractable formulation. Effectiveness of the proposed approach is demonstrated by numerical examples. © 2020 Elsevier Ltd},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents a novel static output feedback stabilization of polynomial systems with bounded actuators. We propose a new sufficient condition for static output feedback design for nominal polynomial systems with constraints on input magnitudes. In the proposed stabilization condition, the system matrices and the Lyapunov matrices are separated, and hence parameterization of the controller is independent of the Lyapunov matrices. The main result is the novel parameter-dependent Lyapunov functions that are readily applied to robust static output feedback design of polynomial systems subject to parametric uncertainty. The proposed design conditions are bilinear in the decision variables. Hence, we provide iterative algorithms to solve the design problems. At each iteration, the design condition is cast as parameter-dependent linear matrix inequalities using the sum-of-squares technique and can be efficiently solved. The proposed approach leads to enhanced static output feedback design with computationally tractable formulation. Effectiveness of the proposed approach is demonstrated by numerical examples. © 2020 Elsevier Ltd
4.
Jennawasin, T; Lin, C -L; Banjerdpongchai, D
Parameter-dependent linear matrix inequality approach to robust state estimation of noisy genetic networks Journal Article
In: Computers and Chemical Engineering, vol. 136, 2020, ISSN: 00981354, (cited By 0).
@article{Jennawasin2020,
title = {Parameter-dependent linear matrix inequality approach to robust state estimation of noisy genetic networks},
author = {T Jennawasin and C -L Lin and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85082009237&doi=10.1016%2fj.compchemeng.2020.106811&partnerID=40&md5=b5fcad72869a5656a52a8a5cc87306f6},
doi = {10.1016/j.compchemeng.2020.106811},
issn = {00981354},
year = {2020},
date = {2020-01-01},
journal = {Computers and Chemical Engineering},
volume = {136},
publisher = {Elsevier Ltd},
abstract = {Genetic networks play an important role in systems biology as they explain the interactions between genes and proteins. However, the genetic networks are described by dynamical systems with nonlinear uncertainties and usually affected by stochastic internal fluctuations, and stochastic external disturbances. The design addressed in this paper is concerned with robust state estimator of stochastic genetic networks in the presence of nonlinear uncertainties. The objective is to estimate the true concentrations of mRNAs and proteins of the noisy nonlinear genetic networks. Based on the notion of Lyapunov functions, we improve the design condition for the robust estimator to ensure that the estimation error satisfies H∞ performance criterion. The sufficient condition is derived in terms of parameter-dependent linear matrix inequalities, which are convex constraints, and can be efficiently solved via the sum-of-squares technique. We provide two numerical examples of real genetic networks to illustrate the effectiveness of the proposed method. © 2020 Elsevier Ltd},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetic networks play an important role in systems biology as they explain the interactions between genes and proteins. However, the genetic networks are described by dynamical systems with nonlinear uncertainties and usually affected by stochastic internal fluctuations, and stochastic external disturbances. The design addressed in this paper is concerned with robust state estimator of stochastic genetic networks in the presence of nonlinear uncertainties. The objective is to estimate the true concentrations of mRNAs and proteins of the noisy nonlinear genetic networks. Based on the notion of Lyapunov functions, we improve the design condition for the robust estimator to ensure that the estimation error satisfies H∞ performance criterion. The sufficient condition is derived in terms of parameter-dependent linear matrix inequalities, which are convex constraints, and can be efficiently solved via the sum-of-squares technique. We provide two numerical examples of real genetic networks to illustrate the effectiveness of the proposed method. © 2020 Elsevier Ltd
5.
Pham, T Van; Nguyen, D H; Banjerdpongchai, D
Consensus synthesis of robust cooperative control for homogeneous leader-follower multi-agent systems subject to parametric uncertainty Journal Article
In: Engineering Journal, vol. 24, no. 3, pp. 169-180, 2020, ISSN: 01258281, (cited By 0).
@article{VanPham2020,
title = {Consensus synthesis of robust cooperative control for homogeneous leader-follower multi-agent systems subject to parametric uncertainty},
author = {T Van Pham and D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086259722&doi=10.4186%2fej.2020.24.3.169&partnerID=40&md5=ac520854b325ffe2a3cf9713f7652a35},
doi = {10.4186/ej.2020.24.3.169},
issn = {01258281},
year = {2020},
date = {2020-01-01},
journal = {Engineering Journal},
volume = {24},
number = {3},
pages = {169-180},
publisher = {Chulalongkorn University, Faculty of Fine and Applied Arts},
abstract = {This paper presents a design of robust consensus for homogeneous leader-follower multi-agent systems (MAS). Each agent of MAS is described by a linear time-invariant dynamic model subject to parametric uncertainty. The agents are interconnected through a static interconnection matrix over an undirected graph to cooperate and share information with their neighbours. The consensus design of MAS can be transformed to stability analysis by using decomposition technique. We apply Lyapunov theorem to derive the sufficient condition to ensure the consensus of all independent subsystems. In addition, we design a robust distributed state feedback gain based on linear quadratic regulator (LQR) setting. Controller gain is computed via solving a linear matrix inequality. As a result, we provide a robust design procedure of a cooperative LQR control to achieve consensus objective and maximize the admissible bound of the uncertainty. Finally, we give numerical examples to illustrate the effectiveness of the proposed consensus design. The results show that the response for MAS in presence of uncertainty using robust consensus design follows the response of the leader and is better than that of the existing nominal consensus design. © 2020, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents a design of robust consensus for homogeneous leader-follower multi-agent systems (MAS). Each agent of MAS is described by a linear time-invariant dynamic model subject to parametric uncertainty. The agents are interconnected through a static interconnection matrix over an undirected graph to cooperate and share information with their neighbours. The consensus design of MAS can be transformed to stability analysis by using decomposition technique. We apply Lyapunov theorem to derive the sufficient condition to ensure the consensus of all independent subsystems. In addition, we design a robust distributed state feedback gain based on linear quadratic regulator (LQR) setting. Controller gain is computed via solving a linear matrix inequality. As a result, we provide a robust design procedure of a cooperative LQR control to achieve consensus objective and maximize the admissible bound of the uncertainty. Finally, we give numerical examples to illustrate the effectiveness of the proposed consensus design. The results show that the response for MAS in presence of uncertainty using robust consensus design follows the response of the leader and is better than that of the existing nominal consensus design. © 2020, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.
6.
Morikawa, T; Wongyimyong, N; Hashikura, K; Suzuki, T; Banjerdpongchai, D; Yamada, K
Parameterization of simultaneously stabilizing controllers for two-stage compensator systems Journal Article
In: ICIC Express Letters, vol. 13, no. 8, pp. 729-734, 2019, ISSN: 1881803X, (cited By 0).
@article{Morikawa2019,
title = {Parameterization of simultaneously stabilizing controllers for two-stage compensator systems},
author = {T Morikawa and N Wongyimyong and K Hashikura and T Suzuki and D Banjerdpongchai and K Yamada},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069440912&doi=10.24507%2ficicel.13.08.729&partnerID=40&md5=45578feed391f4b7b8820f3b5bcd1f98},
doi = {10.24507/icicel.13.08.729},
issn = {1881803X},
year = {2019},
date = {2019-01-01},
journal = {ICIC Express Letters},
volume = {13},
number = {8},
pages = {729-734},
publisher = {ICIC International},
abstract = {This paper aims to show the relationship between compensators which can stabilize a plant in two-stage compensator systems. It is possible to design two-stage compensator systems which are guaranteed to be stable when one of the controllers is broken, and there is changed characteristic of the system depending on input characteristics Previous works have shown the necessary and sufficient conditions for stable two-stage compensator systems but did not give all stabilizing controllers for the systems In this paper, we examine the relationship between controllers which can simultaneously stabilize the plant. © 2019, ICIC International. All rights reserved.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper aims to show the relationship between compensators which can stabilize a plant in two-stage compensator systems. It is possible to design two-stage compensator systems which are guaranteed to be stable when one of the controllers is broken, and there is changed characteristic of the system depending on input characteristics Previous works have shown the necessary and sufficient conditions for stable two-stage compensator systems but did not give all stabilizing controllers for the systems In this paper, we examine the relationship between controllers which can simultaneously stabilize the plant. © 2019, ICIC International. All rights reserved.
7.
Jennawasin, T; Kawanishi, M; Narikiyo, T; Banjerdpongchai, D
Iterative LMI Approach to Robust State-feedback Control of Polynomial Systems with Bounded Actuators Journal Article
In: International Journal of Control, Automation and Systems, vol. 17, no. 4, pp. 847-856, 2019, ISSN: 15986446, (cited By 2).
@article{Jennawasin2019a,
title = {Iterative LMI Approach to Robust State-feedback Control of Polynomial Systems with Bounded Actuators},
author = {T Jennawasin and M Kawanishi and T Narikiyo and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061980543&doi=10.1007%2fs12555-018-0292-6&partnerID=40&md5=d2cc0b2b5a8b5538fb66fd998a45f8fd},
doi = {10.1007/s12555-018-0292-6},
issn = {15986446},
year = {2019},
date = {2019-01-01},
journal = {International Journal of Control, Automation and Systems},
volume = {17},
number = {4},
pages = {847-856},
publisher = {Institute of Control, Robotics and Systems},
abstract = {This paper presents a novel approach to state-feedback stabilization of polynomial systems with bounded actuators. To overcome limitation of the existing approaches, we introduce additional variables that separate the system matrices and the Lyapunov matrices. Therefore, parameterization of the state-feedback controllers is independent of the Lyapunov matrices. The proposed design condition is bilinear in the decision variables, and hence we provide an iterative algorithm to solve the design problem. At each iteration, the design condition is cast as convex optimization using the sum-of-squares technique and can be efficiently solved. In addition, the novel parameter-dependent Lyapunov functions are readily applied to robust state-feedback stabilization of polynomial systems subject to parametric uncertainty. Effectiveness of the proposed approach is demonstrated by numerical examples. © 2019, ICROS, KIEE and Springer.},
note = {cited By 2},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents a novel approach to state-feedback stabilization of polynomial systems with bounded actuators. To overcome limitation of the existing approaches, we introduce additional variables that separate the system matrices and the Lyapunov matrices. Therefore, parameterization of the state-feedback controllers is independent of the Lyapunov matrices. The proposed design condition is bilinear in the decision variables, and hence we provide an iterative algorithm to solve the design problem. At each iteration, the design condition is cast as convex optimization using the sum-of-squares technique and can be efficiently solved. In addition, the novel parameter-dependent Lyapunov functions are readily applied to robust state-feedback stabilization of polynomial systems subject to parametric uncertainty. Effectiveness of the proposed approach is demonstrated by numerical examples. © 2019, ICROS, KIEE and Springer.
8.
Jennawasin, T; Banjerdpongchai, D
Design of state-feedback control for polynomial systems with quadratic performance criterion and control input constraints Journal Article
In: Systems and Control Letters, vol. 117, pp. 53-59, 2018, ISSN: 01676911, (cited By 4).
@article{Jennawasin2018,
title = {Design of state-feedback control for polynomial systems with quadratic performance criterion and control input constraints},
author = {T Jennawasin and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047326920&doi=10.1016%2fj.sysconle.2018.05.004&partnerID=40&md5=5664b92b801c2345c108ad955bbee5b5},
doi = {10.1016/j.sysconle.2018.05.004},
issn = {01676911},
year = {2018},
date = {2018-01-01},
journal = {Systems and Control Letters},
volume = {117},
pages = {53-59},
publisher = {Elsevier B.V.},
abstract = {This paper presents a novel convex optimization approach to design state-feedback control for polynomial systems. Design criteria are comprised of a quadratic cost function and bounded magnitudes of control inputs. Specifically, we formulate a control synthesis of closed-loop systems operated in a given bounded domain characterized by a semi-algebraic set. We consider an extended class of rational Lyapunov functions and derive an upper bound of the cost function, together with a state-feedback control law. By exploiting bounds on the control input magnitudes, the controller design condition can be cast as a parameter-dependent linear matrix inequality (PDLMI), which is convex optimization and can be efficiently solved by sum-of-squares (SOS) technique. In addition, we derive a sufficient condition to compute a lower bound of the cost function. When choosing polynomial structure of the solution candidate, the lower bound can also be written as PDLMI. Numerical examples are provided to illustrate the effectiveness of the proposed design. © 2018 Elsevier B.V.},
note = {cited By 4},
keywords = {},
pubstate = {published},
tppubtype = {article}
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This paper presents a novel convex optimization approach to design state-feedback control for polynomial systems. Design criteria are comprised of a quadratic cost function and bounded magnitudes of control inputs. Specifically, we formulate a control synthesis of closed-loop systems operated in a given bounded domain characterized by a semi-algebraic set. We consider an extended class of rational Lyapunov functions and derive an upper bound of the cost function, together with a state-feedback control law. By exploiting bounds on the control input magnitudes, the controller design condition can be cast as a parameter-dependent linear matrix inequality (PDLMI), which is convex optimization and can be efficiently solved by sum-of-squares (SOS) technique. In addition, we derive a sufficient condition to compute a lower bound of the cost function. When choosing polynomial structure of the solution candidate, the lower bound can also be written as PDLMI. Numerical examples are provided to illustrate the effectiveness of the proposed design. © 2018 Elsevier B.V.
9.
Manusilp, K; Banjerdpongchai, D
Analysis of multi-objective optimal dispatch of cogeneration with thermal energy storage for building energy management system Journal Article
In: Engineering Journal, vol. 21, no. 5, pp. 67-79, 2017, ISSN: 01258281, (cited By 2).
@article{Manusilp2017,
title = {Analysis of multi-objective optimal dispatch of cogeneration with thermal energy storage for building energy management system},
author = {K Manusilp and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032011629&doi=10.4186%2fej.2017.21.5.67&partnerID=40&md5=33e9354e728d4a2ce066ba3879cdc5d6},
doi = {10.4186/ej.2017.21.5.67},
issn = {01258281},
year = {2017},
date = {2017-01-01},
journal = {Engineering Journal},
volume = {21},
number = {5},
pages = {67-79},
publisher = {Chulalongkorn University 1},
abstract = {This paper presents analysis of the multi-objective optimal operation of designed BEMS which contains cogeneration or combined heat and power (CHP) and thermal energy storage (TES) as energy sources. The previously designed BEMS consists of CHP as the main energy supply with absorption chiller and auxiliary boiler. It is observed that there is excessive heat energy from CHP operation which is enough for further utilization. In this paper, TES is additional component to utilize excessive heat energy released from CHP operation. TES cooperates with CHP and auxiliary boiler to supply heat energy to meet the cooling load demand in the building. There are two objective functions for consideration, namely, total operating cost (TOC) and total carbon dioxide emission (TCOE). The multi-objective framework combines both objective functions and employs the weighted sum of TOC and TCOE. Furthermore, we vary initial state of TES from 0-20% of TES’s capacity and analyze its effect on TOC and TCOE. We apply the multi-objective approach to a large shopping mall. Numerical results show that setting initial state of TES to 0% can offer more reduction of TOC and TCOE than other initial conditions. The multi-objective optimal operation converges to minimum TOC when a weighting factor is 0. On the other hand, it converges to the minimum TCOE when the weighting factor is 1. In addition, the trade-off curve showing a relationship between TOC and TCOE provides operating points which depends on operator’s decision criterion. © 2017, Chulalongkorn University 1. All rights reserved.},
note = {cited By 2},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents analysis of the multi-objective optimal operation of designed BEMS which contains cogeneration or combined heat and power (CHP) and thermal energy storage (TES) as energy sources. The previously designed BEMS consists of CHP as the main energy supply with absorption chiller and auxiliary boiler. It is observed that there is excessive heat energy from CHP operation which is enough for further utilization. In this paper, TES is additional component to utilize excessive heat energy released from CHP operation. TES cooperates with CHP and auxiliary boiler to supply heat energy to meet the cooling load demand in the building. There are two objective functions for consideration, namely, total operating cost (TOC) and total carbon dioxide emission (TCOE). The multi-objective framework combines both objective functions and employs the weighted sum of TOC and TCOE. Furthermore, we vary initial state of TES from 0-20% of TES’s capacity and analyze its effect on TOC and TCOE. We apply the multi-objective approach to a large shopping mall. Numerical results show that setting initial state of TES to 0% can offer more reduction of TOC and TCOE than other initial conditions. The multi-objective optimal operation converges to minimum TOC when a weighting factor is 0. On the other hand, it converges to the minimum TCOE when the weighting factor is 1. In addition, the trade-off curve showing a relationship between TOC and TCOE provides operating points which depends on operator’s decision criterion. © 2017, Chulalongkorn University 1. All rights reserved.
10.
Nguyen, D H; Banjerdpongchai, D
Iterative learning control of energy management system: Survey on multi-agent system framework Journal Article
In: Engineering Journal, vol. 20, no. 5, pp. 1-4, 2016, ISSN: 01258281, (cited By 3).
@article{Nguyen2016,
title = {Iterative learning control of energy management system: Survey on multi-agent system framework},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84997218140&doi=10.4186%2fej.2016.20.5.1&partnerID=40&md5=3090f83e98e19265484e5e4fe88f2433},
doi = {10.4186/ej.2016.20.5.1},
issn = {01258281},
year = {2016},
date = {2016-01-01},
journal = {Engineering Journal},
volume = {20},
number = {5},
pages = {1-4},
publisher = {Chulalongkorn University 1},
abstract = {This paper presents a brief survey of recent works on Iterative Learning Control (ILC) of Energy Management System (EMS) based on a framework of Multi-Agent System (MAS). ILC is a control methodology which is especially suitable for dynamical systems whose control tasks are executed in a finite time interval and are repeated over and over. The key idea of ILC is to take available system information in the past and current runs, to generate the control input for the next run. EMS is a computer-based system to monitor energy consumption, control operation, and optimize energy supplies and demands. EMS can be naturally modeled as MAS since each power-generated or powerconsumed component of EMS can be cast as agent. Each agent of MAS is a dynamical system itself and has its own target such as tracking desired trajectory and minimizing energy. Moreover, there are common objectives of EMS which aim to attain its energy efficiency, reliability and optimality. Then one agent can cooperate with other agents to achieve some global objectives, in addition to their own local goals, by exchanging information with other agents. Lastly, we will explore some open research problems and their potential applications. © 2016, Chulalongkorn University 1. All rights reserved.},
note = {cited By 3},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents a brief survey of recent works on Iterative Learning Control (ILC) of Energy Management System (EMS) based on a framework of Multi-Agent System (MAS). ILC is a control methodology which is especially suitable for dynamical systems whose control tasks are executed in a finite time interval and are repeated over and over. The key idea of ILC is to take available system information in the past and current runs, to generate the control input for the next run. EMS is a computer-based system to monitor energy consumption, control operation, and optimize energy supplies and demands. EMS can be naturally modeled as MAS since each power-generated or powerconsumed component of EMS can be cast as agent. Each agent of MAS is a dynamical system itself and has its own target such as tracking desired trajectory and minimizing energy. Moreover, there are common objectives of EMS which aim to attain its energy efficiency, reliability and optimality. Then one agent can cooperate with other agents to achieve some global objectives, in addition to their own local goals, by exchanging information with other agents. Lastly, we will explore some open research problems and their potential applications. © 2016, Chulalongkorn University 1. All rights reserved.
11.
Asawachatroj, A; Banjerdpongchai, D; Busaratragoon, P
Economic assessment of APC and RTO using option to expand Journal Article
In: Engineering Journal, vol. 20, no. 5, pp. 115-134, 2016, ISSN: 01258281, (cited By 1).
@article{Asawachatroj2016,
title = {Economic assessment of APC and RTO using option to expand},
author = {A Asawachatroj and D Banjerdpongchai and P Busaratragoon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84997112335&doi=10.4186%2fej.2016.20.5.115&partnerID=40&md5=37477d6df4a21614f25548d50c1f6957},
doi = {10.4186/ej.2016.20.5.115},
issn = {01258281},
year = {2016},
date = {2016-01-01},
journal = {Engineering Journal},
volume = {20},
number = {5},
pages = {115-134},
publisher = {Chulalongkorn University 1},
abstract = {This paper aims to develop a new economic assessment (EA) method using the option to expand for Advanced Process Control (APC) and Real Time Optimization (RTO). The new EA criteria for investment decision for APC and RTO employ net present value of APC and call option of RTO. Calculation of call option adapts arithmetic measurement method to compute annualized volatility. The new EA applies scenario analysis to take appropriate action. There are four scenarios and their corresponding actions, namely, (1) safe scenario - invest only APC, (2) value-added scenario and (3) risky scenario - invest in APC and RTO, (4) gamble scenario - reject APC. Furthermore, early exercise criterion for RTO investment uses American option method. Applying new EA method to VCM plant demonstrates the effectiveness of the option to expand. The results show that when NPV of APC is negative and the sum of NPV of APC and Call of RTO is positive, APC project is risky scenario. We recommend to invest in APC and RTO. In comparison to conventional NPV and Payback Period (PB) methods, APC is not feasible since NPV is negative and PB is not available due to negative expected profit. In the case study, volatility calculation addresses only one product line in chemical industry which is VCM. Real production comprises of multiple product lines and their volatility is larger than that of one product. With the new EA method, management has comprehensive and flexible tool to assess APC/RTO benefits. Moreover, the new EA provides the timing to invest RTO. Profit margin, expiration period and yield are key parameters that affect early exercise. The new EA is the first method to apply real options to APC and RTO which evaluates the benefit not only APC but also the integrated APC and RTO. The early exercise criterion can facilitate the decision maker to invest in the most beneficial period. © 2016, Chulalongkorn University 1. All rights reserved.},
note = {cited By 1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper aims to develop a new economic assessment (EA) method using the option to expand for Advanced Process Control (APC) and Real Time Optimization (RTO). The new EA criteria for investment decision for APC and RTO employ net present value of APC and call option of RTO. Calculation of call option adapts arithmetic measurement method to compute annualized volatility. The new EA applies scenario analysis to take appropriate action. There are four scenarios and their corresponding actions, namely, (1) safe scenario - invest only APC, (2) value-added scenario and (3) risky scenario - invest in APC and RTO, (4) gamble scenario - reject APC. Furthermore, early exercise criterion for RTO investment uses American option method. Applying new EA method to VCM plant demonstrates the effectiveness of the option to expand. The results show that when NPV of APC is negative and the sum of NPV of APC and Call of RTO is positive, APC project is risky scenario. We recommend to invest in APC and RTO. In comparison to conventional NPV and Payback Period (PB) methods, APC is not feasible since NPV is negative and PB is not available due to negative expected profit. In the case study, volatility calculation addresses only one product line in chemical industry which is VCM. Real production comprises of multiple product lines and their volatility is larger than that of one product. With the new EA method, management has comprehensive and flexible tool to assess APC/RTO benefits. Moreover, the new EA provides the timing to invest RTO. Profit margin, expiration period and yield are key parameters that affect early exercise. The new EA is the first method to apply real options to APC and RTO which evaluates the benefit not only APC but also the integrated APC and RTO. The early exercise criterion can facilitate the decision maker to invest in the most beneficial period. © 2016, Chulalongkorn University 1. All rights reserved.
12.
Nampradit, T; Banjerdpongchai, D
On computing the worst-case h∞ performance of lur'e systems with uncertain time-invariant delays Journal Article
In: Engineering Journal, vol. 19, no. 5, pp. 101-120, 2015, ISSN: 01258281, (cited By 1).
@article{Nampradit2015,
title = {On computing the worst-case h∞ performance of lur'e systems with uncertain time-invariant delays},
author = {T Nampradit and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84947049554&doi=10.4186%2fej.2015.19.5.101&partnerID=40&md5=9e9064832efc12a26758fbfb9177c189},
doi = {10.4186/ej.2015.19.5.101},
issn = {01258281},
year = {2015},
date = {2015-01-01},
journal = {Engineering Journal},
volume = {19},
number = {5},
pages = {101-120},
publisher = {Chulalongkorn University 1},
abstract = {This paper presents a worst-case H∞ performance analysis for Lur'e systems with time-invariant delays. The sufficient condition to guarantee an upper bound of the worst-case performance is developed based on a delay-partitioning Lyapunov-Krasovskii functional containing an integral of sector-bounded nonlinearities. Using Jensen inequality and -procedure, the delay-dependent criterion is given in terms of linear matrix inequalities. In addition, we extend the method to compute an upper bound of the worst-case H∞ performance of Lur'e systems subject to norm-bounded uncertainties by using a matrix eliminating lemma. Numerical results show that our criterion provide the least upper bound on the worst-case performance comparing to the criteria derived based on existing techniques. © 2015, Chulalongkorn University 1. All rights reserved.},
note = {cited By 1},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents a worst-case H∞ performance analysis for Lur'e systems with time-invariant delays. The sufficient condition to guarantee an upper bound of the worst-case performance is developed based on a delay-partitioning Lyapunov-Krasovskii functional containing an integral of sector-bounded nonlinearities. Using Jensen inequality and -procedure, the delay-dependent criterion is given in terms of linear matrix inequalities. In addition, we extend the method to compute an upper bound of the worst-case H∞ performance of Lur'e systems subject to norm-bounded uncertainties by using a matrix eliminating lemma. Numerical results show that our criterion provide the least upper bound on the worst-case performance comparing to the criteria derived based on existing techniques. © 2015, Chulalongkorn University 1. All rights reserved.
13.
Nampradit, T; Banjerdpongchai, D
Iterative LMI approach to design robust state-feedback controllers for Lur’e systems with time-invariant delays Journal Article
In: International Journal of Control, Automation and Systems, vol. 13, no. 5, pp. 1086-1096, 2015, ISSN: 15986446, (cited By 0).
@article{Nampradit2015a,
title = {Iterative LMI approach to design robust state-feedback controllers for Lur’e systems with time-invariant delays},
author = {T Nampradit and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84942505309&doi=10.1007%2fs12555-014-0103-7&partnerID=40&md5=a424b1cdcee73b997f74c728442042af},
doi = {10.1007/s12555-014-0103-7},
issn = {15986446},
year = {2015},
date = {2015-01-01},
journal = {International Journal of Control, Automation and Systems},
volume = {13},
number = {5},
pages = {1086-1096},
publisher = {Institute of Control, Robotics and Systems},
abstract = {In this paper, we present a design of robust state-feedback stabilization and a design of robust state-feedback H∞ control for Lur’e systems with time-invariant delays and norm-bounded uncertainties. The criteria of state-feedback stabilization and state-feedback H∞ control are developed using Lyapunov-Krasovskii Theorem with a delay-partitioning Lyapunov-Krasovskii functional and an integral of sector-bounded nonlinearities. The design criteria are given in terms of bilinear matrix inequality, which is non-convex optimization. We develop algorithms based on coordinate optimization, which alternate between two LMI optimization problems, to solve for the robust state-feedback controllers. The proposed iterative LMI algorithm for H∞ control design is a local optimization procedure, but it can return satisfactory state-feedback controllers depending on the initialization. Numerical examples show that the proposed LMI algorithms can provide robust state-feedback stabilization to guarantee the closed-loop stability of LSTD and yield robust state-feedback control to guarantee the worstcase H∞ performance of the closed-loop LSTD. © 2015, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present a design of robust state-feedback stabilization and a design of robust state-feedback H∞ control for Lur’e systems with time-invariant delays and norm-bounded uncertainties. The criteria of state-feedback stabilization and state-feedback H∞ control are developed using Lyapunov-Krasovskii Theorem with a delay-partitioning Lyapunov-Krasovskii functional and an integral of sector-bounded nonlinearities. The design criteria are given in terms of bilinear matrix inequality, which is non-convex optimization. We develop algorithms based on coordinate optimization, which alternate between two LMI optimization problems, to solve for the robust state-feedback controllers. The proposed iterative LMI algorithm for H∞ control design is a local optimization procedure, but it can return satisfactory state-feedback controllers depending on the initialization. Numerical examples show that the proposed LMI algorithms can provide robust state-feedback stabilization to guarantee the closed-loop stability of LSTD and yield robust state-feedback control to guarantee the worstcase H∞ performance of the closed-loop LSTD. © 2015, Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.
14.
Asawachatroj, A; Banjerdpongchai, D; Busaratragoon, P
Enhancement of investment decision making using real options with application to advanced process control project Journal Article
In: Engineering Journal, vol. 18, no. 3, pp. 37-54, 2014, ISSN: 01258281, (cited By 2).
@article{Asawachatroj2014,
title = {Enhancement of investment decision making using real options with application to advanced process control project},
author = {A Asawachatroj and D Banjerdpongchai and P Busaratragoon},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904331167&doi=10.4186%2fej.2014.18.3.37&partnerID=40&md5=79d59ccbfb9a2932e2f481f182c844e0},
doi = {10.4186/ej.2014.18.3.37},
issn = {01258281},
year = {2014},
date = {2014-01-01},
journal = {Engineering Journal},
volume = {18},
number = {3},
pages = {37-54},
publisher = {Chulalongkorn University},
abstract = {Feasibility study is one of the most important parts of decision making for project investment. Current industrial approach to estimate benefit of advanced process control (APC) is based on the conventional estimation techniques, namely, statistical analysis, net present value, and payback period. These conventional approaches can answer the investment either 'Go' or 'No Go'. The gap analysis reveals that economic uncertainties and inflexibility of decision criteria are the issues required improvement on the decision making process. In this paper, we apply a real options approach to develop option to defer analysis as part of the proposed feasibility study of APC project. We demonstrate improvement of the proposed method with a case study on ethylene plant in Thailand. The result shows that option to defer can answer 'when to defer' and 'when to invest'. Hence, this approach enhances the investment decision making under economic uncertainties and provides flexible decision criteria.},
note = {cited By 2},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Feasibility study is one of the most important parts of decision making for project investment. Current industrial approach to estimate benefit of advanced process control (APC) is based on the conventional estimation techniques, namely, statistical analysis, net present value, and payback period. These conventional approaches can answer the investment either 'Go' or 'No Go'. The gap analysis reveals that economic uncertainties and inflexibility of decision criteria are the issues required improvement on the decision making process. In this paper, we apply a real options approach to develop option to defer analysis as part of the proposed feasibility study of APC project. We demonstrate improvement of the proposed method with a case study on ethylene plant in Thailand. The result shows that option to defer can answer 'when to defer' and 'when to invest'. Hence, this approach enhances the investment decision making under economic uncertainties and provides flexible decision criteria.
15.
Nampradit, T; Banjerdpongchai, D
On computing maximum allowable time delay of Lur'e systems with uncertain time-invariant delays Journal Article
In: International Journal of Control, Automation and Systems, vol. 12, no. 3, pp. 497-506, 2014, ISSN: 15986446, (cited By 4).
@article{Nampradit2014,
title = {On computing maximum allowable time delay of Lur'e systems with uncertain time-invariant delays},
author = {T Nampradit and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84901032921&doi=10.1007%2fs12555-013-0433-x&partnerID=40&md5=c347318e4283532d4b916d6289fce059},
doi = {10.1007/s12555-013-0433-x},
issn = {15986446},
year = {2014},
date = {2014-01-01},
journal = {International Journal of Control, Automation and Systems},
volume = {12},
number = {3},
pages = {497-506},
publisher = {Institute of Control, Robotics and Systems},
abstract = {In this paper, we present an improved delay-dependent absolute stability criterion for Lur'e systems with time delays. The guarantee of absolute stability is provided by Lyapunov-Krasovskii theorem with the Lyapunov functional containing the integral of sector-bounded nonlinearities. The Lyapunov functional terms involving delay are partitioned to be associated with each equidistant fragment on the length of time delay. Employing the Jensen inequality and S-procedure, the sufficient condition is derived from time derivative of the Lyapunov functional. Then, the absolute stability criterion expressed in terms of linear matrix inequalities (LMIs) can be efficiently solved using available LMI solvers. The bisection method is used to determine the maximum allowable time delays to ensure the stability of Lur'e systems in the presence of uncertain time-invariant delays. In addition, the stability criterion is extended to Lur'e systems subject to norm-bounded uncertainties by using the matrix eliminating lemma. Numerical results from two benchmark problems show that the proposed criteria give significant improvement on the maximum allowable time delays. © 2014 Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.},
note = {cited By 4},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present an improved delay-dependent absolute stability criterion for Lur'e systems with time delays. The guarantee of absolute stability is provided by Lyapunov-Krasovskii theorem with the Lyapunov functional containing the integral of sector-bounded nonlinearities. The Lyapunov functional terms involving delay are partitioned to be associated with each equidistant fragment on the length of time delay. Employing the Jensen inequality and S-procedure, the sufficient condition is derived from time derivative of the Lyapunov functional. Then, the absolute stability criterion expressed in terms of linear matrix inequalities (LMIs) can be efficiently solved using available LMI solvers. The bisection method is used to determine the maximum allowable time delays to ensure the stability of Lur'e systems in the presence of uncertain time-invariant delays. In addition, the stability criterion is extended to Lur'e systems subject to norm-bounded uncertainties by using the matrix eliminating lemma. Numerical results from two benchmark problems show that the proposed criteria give significant improvement on the maximum allowable time delays. © 2014 Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag Berlin Heidelberg.
16.
Petkajee, T; Banjerdpongchai, D
Design of cogeneration and analysis of economic and environmental optimal operations for building energy management system Journal Article
In: ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 11, no. 2, pp. 79-94, 2013, ISSN: 16859545, (cited By 3).
@article{Petkajee2013a,
title = {Design of cogeneration and analysis of economic and environmental optimal operations for building energy management system},
author = {T Petkajee and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904802829&partnerID=40&md5=2f44be822abdae49cb03ad393a0bcb7c},
issn = {16859545},
year = {2013},
date = {2013-01-01},
journal = {ECTI Transactions on Electrical Engineering, Electronics, and Communications},
volume = {11},
number = {2},
pages = {79-94},
publisher = {ECTI Association},
abstract = {This paper proposes a design of cogeneration or combined heat and power (CHP) system and analysis of economic and environmental optimal operations for a building energy management system (BEMS). The proposed BEMS consists of a CHP system, an auxiliary boiler, an absorption chiller, and power grids. The design problem concerns with multi-objective cost functions: total operating costs (TOC) and total carbon dioxide emissions (TCOE) which can be formulated as a linear program. The optimal operation analysis is employed to determine a suitable capacity of the CHP system for the proposed BEMS. Then, we analyze the optimal energy flow for each component and the relationship between TOC and TCOE. The numerical results show that the proposed BEMS can reduce both TOC and TCOE up to 30% and 14%, compared to the original electricity usage. Furthermore, the simulation is extended to determine risk in a long-term operation by investigating the impact of fuel prices to TOC and TCOE.},
note = {cited By 3},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper proposes a design of cogeneration or combined heat and power (CHP) system and analysis of economic and environmental optimal operations for a building energy management system (BEMS). The proposed BEMS consists of a CHP system, an auxiliary boiler, an absorption chiller, and power grids. The design problem concerns with multi-objective cost functions: total operating costs (TOC) and total carbon dioxide emissions (TCOE) which can be formulated as a linear program. The optimal operation analysis is employed to determine a suitable capacity of the CHP system for the proposed BEMS. Then, we analyze the optimal energy flow for each component and the relationship between TOC and TCOE. The numerical results show that the proposed BEMS can reduce both TOC and TCOE up to 30% and 14%, compared to the original electricity usage. Furthermore, the simulation is extended to determine risk in a long-term operation by investigating the impact of fuel prices to TOC and TCOE.
17.
Khaisongkram, W; Banjerdpongchai, D
A branch-and-bound algorithm to compute the worst-case norm of uncertain linear systems under inputs with magnitude and rate constraints Journal Article
In: International Journal of Control, Automation and Systems, vol. 10, no. 3, pp. 449-458, 2012, ISSN: 15986446, (cited By 0).
@article{Khaisongkram2012,
title = {A branch-and-bound algorithm to compute the worst-case norm of uncertain linear systems under inputs with magnitude and rate constraints},
author = {W Khaisongkram and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84866002197&doi=10.1007%2fs12555-012-0301-0&partnerID=40&md5=1e9ce911e36c72181ef0de8a383f9c22},
doi = {10.1007/s12555-012-0301-0},
issn = {15986446},
year = {2012},
date = {2012-01-01},
journal = {International Journal of Control, Automation and Systems},
volume = {10},
number = {3},
pages = {449-458},
abstract = {This paper extends the worst-case norm (WCN) of linear systems subject to inputs with magnitude and rate bounds to the WCN of uncertain linear systems under the same inputs. While the WCN for linear systems can be accurately approximated by simply solving a sparse linear programming, the computation of the WCN for uncertain linear systems leads to an NP-hard problem. In this paper, a branch-and-bound algorithm is applied to calculate the WCN in the presence of uncertainty. Subsequently, we derive the bounds for two approximation errors, namely, the truncation error and the discretization error, which are resulted from the proposed WCN computation method. Based on these error bounds, we give a brief guideline for choosing appropriate values of the terminal time and the sampling time. Numerical examples demonstate that computation time of the proposed algorithm is reasonable within certain problem dimensions. An exhaustive search is employed to validate the branch-and-bound algorithm. Finally, we suggest a means to improve the WCN computation for problems with higher dimension. © ICROS, KIEE and Springer 2012;.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper extends the worst-case norm (WCN) of linear systems subject to inputs with magnitude and rate bounds to the WCN of uncertain linear systems under the same inputs. While the WCN for linear systems can be accurately approximated by simply solving a sparse linear programming, the computation of the WCN for uncertain linear systems leads to an NP-hard problem. In this paper, a branch-and-bound algorithm is applied to calculate the WCN in the presence of uncertainty. Subsequently, we derive the bounds for two approximation errors, namely, the truncation error and the discretization error, which are resulted from the proposed WCN computation method. Based on these error bounds, we give a brief guideline for choosing appropriate values of the terminal time and the sampling time. Numerical examples demonstate that computation time of the proposed algorithm is reasonable within certain problem dimensions. An exhaustive search is employed to validate the branch-and-bound algorithm. Finally, we suggest a means to improve the WCN computation for problems with higher dimension. © ICROS, KIEE and Springer 2012;.
18.
Nguyen, D H; Banjerdpongchai, D
A convex optimization approach to robust iterative learning control for linear systems with time-varying parametric uncertainties Journal Article
In: Automatica, vol. 47, no. 9, pp. 2039-2043, 2011, ISSN: 00051098, (cited By 25).
@article{Nguyen2011,
title = {A convex optimization approach to robust iterative learning control for linear systems with time-varying parametric uncertainties},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052026272&doi=10.1016%2fj.automatica.2011.05.022&partnerID=40&md5=86a529738671e6c040dc4da2c441b6c5},
doi = {10.1016/j.automatica.2011.05.022},
issn = {00051098},
year = {2011},
date = {2011-01-01},
journal = {Automatica},
volume = {47},
number = {9},
pages = {2039-2043},
abstract = {In this paper, we present a new robust iterative learning control (ILC) design for a class of linear systems in the presence of time-varying parametric uncertainties and additive input/output disturbances. The system model is described by the Markov matrix as an affine function of parametric uncertainties. The robust ILC design is formulated as a minmax problem using a quadratic performance criterion subject to constraints of the control input update. Then, we propose a novel methodology to find a suboptimal solution of the minmax optimization problem. First, we derive an upper bound of the worst-case performance. As a result, the minmax problem is relaxed to become a minimization problem in the form of a quadratic program. Next, the robust ILC design is cast into a convex optimization over linear matrix inequalities (LMIs) which can be easily solved using off-the-shelf optimization solvers. The convergences of the control input and the error are proved. Finally, the robust ILC algorithm is applied to a physical model of a flexible link. The simulation results reveal the effectiveness of the proposed algorithm. © 2011 Elsevier Ltd. All rights reserved.},
note = {cited By 25},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present a new robust iterative learning control (ILC) design for a class of linear systems in the presence of time-varying parametric uncertainties and additive input/output disturbances. The system model is described by the Markov matrix as an affine function of parametric uncertainties. The robust ILC design is formulated as a minmax problem using a quadratic performance criterion subject to constraints of the control input update. Then, we propose a novel methodology to find a suboptimal solution of the minmax optimization problem. First, we derive an upper bound of the worst-case performance. As a result, the minmax problem is relaxed to become a minimization problem in the form of a quadratic program. Next, the robust ILC design is cast into a convex optimization over linear matrix inequalities (LMIs) which can be easily solved using off-the-shelf optimization solvers. The convergences of the control input and the error are proved. Finally, the robust ILC algorithm is applied to a physical model of a flexible link. The simulation results reveal the effectiveness of the proposed algorithm. © 2011 Elsevier Ltd. All rights reserved.
19.
Nguyen, D H; Banjerdpongchai, D
Robust iterative learning control for linear systems subject to time-invariant parametric uncertainties and repetitive disturbances Journal Article
In: ECTI Transactions on Electrical Engineering, Electronics, and Communications, vol. 9, no. 1, pp. 169-176, 2011, ISSN: 16859545, (cited By 0).
@article{Nguyen2011a,
title = {Robust iterative learning control for linear systems subject to time-invariant parametric uncertainties and repetitive disturbances},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80055092595&partnerID=40&md5=2e8e53f44ba0f94cf22a59e53b32ab96},
issn = {16859545},
year = {2011},
date = {2011-01-01},
journal = {ECTI Transactions on Electrical Engineering, Electronics, and Communications},
volume = {9},
number = {1},
pages = {169-176},
publisher = {ECTI Association},
abstract = {This paper presents the design of a robust Iterative Learning Control (ILC) algorithm for linear systems in the presence of parametric uncertainties and repet-itive disturbances. The robust ILC design is formu-lated as a min-max problem with a quadratic perfor-mance index subjected to constraints of the control input. Employing Lagrange duality, we can refor-mulate the robust ILC design as a convex optimiza-tion problem over linear matrix inequalities (LMIs). An LMI algorithm for the robust ILC design is then given. Finally, the effectiveness of the proposed ro-bust ILC algorithm is demonstrated through a nu-merical example.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents the design of a robust Iterative Learning Control (ILC) algorithm for linear systems in the presence of parametric uncertainties and repet-itive disturbances. The robust ILC design is formu-lated as a min-max problem with a quadratic perfor-mance index subjected to constraints of the control input. Employing Lagrange duality, we can refor-mulate the robust ILC design as a convex optimiza-tion problem over linear matrix inequalities (LMIs). An LMI algorithm for the robust ILC design is then given. Finally, the effectiveness of the proposed ro-bust ILC algorithm is demonstrated through a nu-merical example.
20.
Nguyen, D H; Banjerdpongchai, D
A convex optimization design of robust iterative learning control for linear systems with iteration-varying parametric uncertainties Journal Article
In: Asian Journal of Control, vol. 13, no. 1, pp. 75-84, 2011, ISSN: 15618625, (cited By 9).
@article{Nguyen2011b,
title = {A convex optimization design of robust iterative learning control for linear systems with iteration-varying parametric uncertainties},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79953816266&doi=10.1002%2fasjc.266&partnerID=40&md5=c6b7311b39c076ff7be58e88f3539b0b},
doi = {10.1002/asjc.266},
issn = {15618625},
year = {2011},
date = {2011-01-01},
journal = {Asian Journal of Control},
volume = {13},
number = {1},
pages = {75-84},
abstract = {In this paper, a new robust iterative learning control (ILC) algorithm has been proposed for linear systems in the presence of iteration-varying parametric uncertainties. The robust ILC design is formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update. An upper bound of the maximization problem is derived, then, the solution of the min-max problem is achieved by solving a minimization problem. Applying Lagrangian duality to this minimization problem results in a dual problem which can be reformulated as a convex optimization problem over linear matrix inequalities (LMIs). Next, we present an LMI-based algorithm for the robust ILC design and prove the convergence of the control input and the error. Finally, the proposed algorithm is applied to a distillation column to demonstrate its effectiveness. © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society.},
note = {cited By 9},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, a new robust iterative learning control (ILC) algorithm has been proposed for linear systems in the presence of iteration-varying parametric uncertainties. The robust ILC design is formulated as a min-max problem using a quadratic performance criterion subject to constraints of the control input update. An upper bound of the maximization problem is derived, then, the solution of the min-max problem is achieved by solving a minimization problem. Applying Lagrangian duality to this minimization problem results in a dual problem which can be reformulated as a convex optimization problem over linear matrix inequalities (LMIs). Next, we present an LMI-based algorithm for the robust ILC design and prove the convergence of the control input and the error. Finally, the proposed algorithm is applied to a distillation column to demonstrate its effectiveness. © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society.
21.
Nguyen, D H; Banjerdpongchai, D
Robust iterative learning control for linear systems with multiple time-invariant parametric uncertainties Journal Article
In: International Journal of Control, vol. 83, no. 12, pp. 2506-2518, 2010, ISSN: 00207179, (cited By 0).
@article{Nguyen2010,
title = {Robust iterative learning control for linear systems with multiple time-invariant parametric uncertainties},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650340270&doi=10.1080%2f00207179.2010.531398&partnerID=40&md5=fb73875d339ae509adc39707f4ad3265},
doi = {10.1080/00207179.2010.531398},
issn = {00207179},
year = {2010},
date = {2010-01-01},
journal = {International Journal of Control},
volume = {83},
number = {12},
pages = {2506-2518},
abstract = {This article presents a novel robust iterative learning control algorithm (ILC) for linear systems in the presence of multiple time-invariant parametric uncertainties.The robust design problem is formulated as a min-max problem with a quadratic performance criterion subject to constraints of the iterative control input update. Then, we propose a new methodology to find a sub-optimal solution of the min-max problem. By finding an upper bound of the worst-case performance, the min-max problem is relaxed to be a minimisation problem. Applying Lagrangian duality to this minimisation problem leads to a dual problem which can be reformulated as a convex optimisation problem over linear matrix inequalities (LMIs). An LMI-based ILC algorithm is given afterward and the convergence of the control input as well as the system error are proved. Finally, we apply the proposed ILC to a generic example and a distillation column. The numerical results reveal the effectiveness of the LMI-based algorithm. © 2010 Taylor & Francis.},
note = {cited By 0},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This article presents a novel robust iterative learning control algorithm (ILC) for linear systems in the presence of multiple time-invariant parametric uncertainties.The robust design problem is formulated as a min-max problem with a quadratic performance criterion subject to constraints of the iterative control input update. Then, we propose a new methodology to find a sub-optimal solution of the min-max problem. By finding an upper bound of the worst-case performance, the min-max problem is relaxed to be a minimisation problem. Applying Lagrangian duality to this minimisation problem leads to a dual problem which can be reformulated as a convex optimisation problem over linear matrix inequalities (LMIs). An LMI-based ILC algorithm is given afterward and the convergence of the control input as well as the system error are proved. Finally, we apply the proposed ILC to a generic example and a distillation column. The numerical results reveal the effectiveness of the LMI-based algorithm. © 2010 Taylor & Francis.
22.
Nguyen, D H; Banjerdpongchai, D
An LMI approach for robust iterative learning control with quadratic performance criterion Journal Article
In: Journal of Process Control, vol. 19, no. 6, pp. 1054-1060, 2009, ISSN: 09591524, (cited By 25).
@article{Nguyen2009b,
title = {An LMI approach for robust iterative learning control with quadratic performance criterion},
author = {D H Nguyen and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-67349219676&doi=10.1016%2fj.jprocont.2008.12.004&partnerID=40&md5=ec8b8ea7bdb4d7e3c5d6da3d68f87a01},
doi = {10.1016/j.jprocont.2008.12.004},
issn = {09591524},
year = {2009},
date = {2009-01-01},
journal = {Journal of Process Control},
volume = {19},
number = {6},
pages = {1054-1060},
abstract = {This paper presents the design of iterative learning control based on quadratic performance criterion (Q-ILC) for linear systems subject to additive uncertainty. The robust Q-ILC design can be cast as a min-max problem. We propose a novel approach which employs an upper bound of the worst-case performance, then formulates a non-convex quadratic minimization problem to get the update of iterative control inputs. Applying Lagrange duality, the Lagrange dual function of the non-convex quadratic problem is equivalent to a convex optimization over linear matrix inequalities (LMIs). An LMI algorithm with convergence properties is then given for the robust Q-ILC design. Finally, we provide a numerical example to illustrate the effectiveness of the proposed method. © 2008 Elsevier Ltd. All rights reserved.},
note = {cited By 25},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper presents the design of iterative learning control based on quadratic performance criterion (Q-ILC) for linear systems subject to additive uncertainty. The robust Q-ILC design can be cast as a min-max problem. We propose a novel approach which employs an upper bound of the worst-case performance, then formulates a non-convex quadratic minimization problem to get the update of iterative control inputs. Applying Lagrange duality, the Lagrange dual function of the non-convex quadratic problem is equivalent to a convex optimization over linear matrix inequalities (LMIs). An LMI algorithm with convergence properties is then given for the robust Q-ILC design. Finally, we provide a numerical example to illustrate the effectiveness of the proposed method. © 2008 Elsevier Ltd. All rights reserved.
23.
Khaisongkram, W; Banjerdpongchai, D
On computing the worst-case norm of linear systems subject to inputs with magnitude bound and rate limit Journal Article
In: International Journal of Control, vol. 80, no. 2, pp. 190-219, 2007, ISSN: 00207179, (cited By 7).
@article{Khaisongkram2007,
title = {On computing the worst-case norm of linear systems subject to inputs with magnitude bound and rate limit},
author = {W Khaisongkram and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33751164188&doi=10.1080%2f00207170600951612&partnerID=40&md5=e617f6cd6ce0756ee0b25340a7f65e86},
doi = {10.1080/00207170600951612},
issn = {00207179},
year = {2007},
date = {2007-01-01},
journal = {International Journal of Control},
volume = {80},
number = {2},
pages = {190-219},
abstract = {In this paper, we propose a practical and effective approach to compute the worst-case norm of finite-dimensional convolution systems. System inputs are modelled to have bounded magnitude and rate limit. The computation of the worst-case norm is formulated as a fixed-terminal-time optimal control problem. Applying Pontryagin's maximum principle with the generalized Karush-Kuhn-Tucker theorem, we obtain necessary conditions which are subsequently exploited to characterize the worst-case input. Furthermore, we develop a novel algorithm called successive pang interval search (SPIS) to construct the worst-case input for general finite-dimensional convolution systems. The algorithm is guaranteed to converge and give an accurate solution within a prescribed error bound. To verify the accuracy of the algorithm, we derive bounds on computational errors including the truncation error and the discretization error. Then, the bounds on the errors yielded by our algorithm are compared with those of a comparative discrete-time method. This suggests that SPIS is deemed to be more accurate, analytically. Numerical results based on second-order linear systems show that both approaches give the worst-case norms with comparable errors, but SPIS requires much less computation time than the discrete-time method.},
note = {cited By 7},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we propose a practical and effective approach to compute the worst-case norm of finite-dimensional convolution systems. System inputs are modelled to have bounded magnitude and rate limit. The computation of the worst-case norm is formulated as a fixed-terminal-time optimal control problem. Applying Pontryagin's maximum principle with the generalized Karush-Kuhn-Tucker theorem, we obtain necessary conditions which are subsequently exploited to characterize the worst-case input. Furthermore, we develop a novel algorithm called successive pang interval search (SPIS) to construct the worst-case input for general finite-dimensional convolution systems. The algorithm is guaranteed to converge and give an accurate solution within a prescribed error bound. To verify the accuracy of the algorithm, we derive bounds on computational errors including the truncation error and the discretization error. Then, the bounds on the errors yielded by our algorithm are compared with those of a comparative discrete-time method. This suggests that SPIS is deemed to be more accurate, analytically. Numerical results based on second-order linear systems show that both approaches give the worst-case norms with comparable errors, but SPIS requires much less computation time than the discrete-time method.
24.
Khaisongkram, W; Banjerdpongchai, D
In: Journal of Process Control, vol. 16, no. 8, pp. 845-854, 2006, ISSN: 09591524, (cited By 5).
@article{Khaisongkram2006a,
title = {Linear controller design and performance limits of binary distillation column subject to disturbances with bounds on magnitudes and rates of change},
author = {W Khaisongkram and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33746215053&doi=10.1016%2fj.jprocont.2006.02.005&partnerID=40&md5=48a3c8067b9665ed8243f94fe6fea576},
doi = {10.1016/j.jprocont.2006.02.005},
issn = {09591524},
year = {2006},
date = {2006-01-01},
journal = {Journal of Process Control},
volume = {16},
number = {8},
pages = {845-854},
abstract = {In this paper, we present an application of linear controller design via convex optimization to a binary distillation column and determine its limits of performance. Disturbances of distillation process are characterized as input signals with bounded magnitudes and rates of change. Performance measures of top and bottom control loops are defined as the maximum deviation magnitudes of top and bottom compositions, respectively. This performance is often referred to as the worst-case norm of convolution systems under such disturbances. The convex optimization and the ellipsoid algorithm are applied to design linear controllers and, at the same time, determine the best achievable performance of the closed-loop system. Then, a series of convex optimization problems are efficiently solved to give a trade-off curve representing limits of performance between the top and bottom compositions. The trade-off curve provides a practical insight into the design specification that cannot be achieved for the distillation column control with dynamic controller configuration. To confirm the results, we undertake computer simulation using nonlinear dynamical model of the distillation column. Closed-loop responses of the chosen optimal linear controller are consistent with the trade-off curve and yields superior performance than that of a conventional decentralized PI controller. © 2006 Elsevier Ltd. All rights reserved.},
note = {cited By 5},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In this paper, we present an application of linear controller design via convex optimization to a binary distillation column and determine its limits of performance. Disturbances of distillation process are characterized as input signals with bounded magnitudes and rates of change. Performance measures of top and bottom control loops are defined as the maximum deviation magnitudes of top and bottom compositions, respectively. This performance is often referred to as the worst-case norm of convolution systems under such disturbances. The convex optimization and the ellipsoid algorithm are applied to design linear controllers and, at the same time, determine the best achievable performance of the closed-loop system. Then, a series of convex optimization problems are efficiently solved to give a trade-off curve representing limits of performance between the top and bottom compositions. The trade-off curve provides a practical insight into the design specification that cannot be achieved for the distillation column control with dynamic controller configuration. To confirm the results, we undertake computer simulation using nonlinear dynamical model of the distillation column. Closed-loop responses of the chosen optimal linear controller are consistent with the trade-off curve and yields superior performance than that of a conventional decentralized PI controller. © 2006 Elsevier Ltd. All rights reserved.
25.
Khaisongkram, W; Banjerdpongchai, D
MATLAB based GUIs for linear controller design via convex optimization Journal Article
In: Computer Applications in Engineering Education, vol. 11, no. 1, pp. 13-24, 2003, ISSN: 10613773, (cited By 8).
@article{Khaisongkram2003,
title = {MATLAB based GUIs for linear controller design via convex optimization},
author = {W Khaisongkram and D Banjerdpongchai},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33747073718&doi=10.1002%2fcae.10035&partnerID=40&md5=2b7fca4e343164c0d9f34250ce1c553b},
doi = {10.1002/cae.10035},
issn = {10613773},
year = {2003},
date = {2003-01-01},
journal = {Computer Applications in Engineering Education},
volume = {11},
number = {1},
pages = {13-24},
abstract = {Owing to the current evolution of computational tools, a complicated parameter optimization problem could be effectively solved by a computer. In this paper, a CAD tool for multi-objective controller design based on MATLAB program is developed. In addition, we construct simple GUIs (using GUIDE tools within MATLAB) to provide a visual approach in specifying the constraints. The linear controller design problem can be cast as the convex optimization subjected to time domain and frequency domain constraints. This optimization problem is efficiently solved within a finite dimensional subspace by a practical ellipsoid algorithm. In the design process, we include a model reduction of the resulting controller to speed up the computational efficiency. Finally, a numerical example shows the capability of the program to design multi-objective controller for a one-link flexible robot arm. © 2003 Wiley Periodicals, Inc.},
note = {cited By 8},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Owing to the current evolution of computational tools, a complicated parameter optimization problem could be effectively solved by a computer. In this paper, a CAD tool for multi-objective controller design based on MATLAB program is developed. In addition, we construct simple GUIs (using GUIDE tools within MATLAB) to provide a visual approach in specifying the constraints. The linear controller design problem can be cast as the convex optimization subjected to time domain and frequency domain constraints. This optimization problem is efficiently solved within a finite dimensional subspace by a practical ellipsoid algorithm. In the design process, we include a model reduction of the resulting controller to speed up the computational efficiency. Finally, a numerical example shows the capability of the program to design multi-objective controller for a one-link flexible robot arm. © 2003 Wiley Periodicals, Inc.