Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA

Jiing-Dong HWANG; Zhi-Ren TSAI

doi:10.1587/transfun.E92.A.2266

Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA

Jiing-Dong HWANG, Zhi-Ren TSAI

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This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H_∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E92-A No.9 pp.2266-2274

Publication Date: 2009/09/01

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Online ISSN: 1745-1337

DOI: 10.1587/transfun.E92.A.2266

Type of Manuscript: PAPER

Category: Systems and Control

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Jiing-Dong HWANG, Zhi-Ren TSAI, "Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA" in IEICE TRANSACTIONS on Fundamentals, vol. E92-A, no. 9, pp. 2266-2274, September 2009, doi: 10.1587/transfun.E92.A.2266.
Abstract: This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H_∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.2266/_p

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@ARTICLE{e92-a_9_2266,
author={Jiing-Dong HWANG, Zhi-Ren TSAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA},
year={2009},
volume={E92-A},
number={9},
pages={2266-2274},
abstract={This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H_∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.},
keywords={},
doi={10.1587/transfun.E92.A.2266},
ISSN={1745-1337},
month={September},}

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TY - JOUR
TI - Adaptive Tracker Design with Identifier for Pendulum System by Conditional LMI Method and IROA
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2266
EP - 2274
AU - Jiing-Dong HWANG
AU - Zhi-Ren TSAI
PY - 2009
DO - 10.1587/transfun.E92.A.2266
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2009
AB - This paper proposes a robust adaptive fuzzy PID control scheme augmented with a supervisory controller for unknown systems. In this scheme, a generalized fuzzy model is used to describe a class of unknown systems. The control strategy allows each part of the control law, i.e., a supervisory controller, a compensator, and an adaptive fuzzy PID controller, to be designed incrementally according to different guidelines. The supervisory controller in the outer loop aims at enhancing system robustness in the face of extra disturbances, variation in system parameters, and parameter drift in the adaptation law. Furthermore, an H_∞ control design method using the fuzzy Lyapunov function is presented for the design of the initial control gains that guarantees transient performance at the start of closed-loop control, which is generally overlooked in many adaptive control systems. This design of the initial control gains is a compound search strategy called conditional linear matrix inequality (CLMI) approach with IROA (Improved random optimal algorithm), it leads to less complex designs than a standard LMI method by fuzzy Lyapunov function. Numerical studies of the tracking control of an uncertain inverted pendulum system demonstrate the effectiveness of the control strategy. From results of this simulation, the generalized fuzzy model reduces the rule number of T-S fuzzy model indeed.
ER -