Browsing by Author "Hsiao, Feng-Hsiag"

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Decentralized stabilization of H-infinity fuzzy control for nonlinear multiple time-delay interconnected systems
(2007-03-01)
Hsiao, Feng-Hsiag
;
Xu, Sheng-Dong
;
Lin, Chia-Yen
;
Chou, Yu-Jun
;
Chen, Yu-Ching
A robustness design of H infinity fuzzy control is proposed in this paper to overcome the effect of modeling errors between nonlinear multiple time-delay systems and fuzzy models. In terms of Lyapunov's direct method, a stability criterion is derived to guarantee the UUB (uniformly ultimately bounded) stability of nonlinear multiple time-delay interconnected systems with disturbances. Based on this criterion and the decentralized control scheme, a set of fuzzy controllers is then synthesized via the technique of parallel distributed compensation (PDC) to stabilize the nonlinear multiple time-delay interconnected systems and the H infinity control performance is achieved in the mean time.
Decentralized stabilization of neural network linearly interconnected systems via T-S fuzzy control
(2007-05-01)
Hsiao, Feng-Hsiag
;
Liang, Yew-Wen
;
Xu, Sheng-Dong
;
Lee, Gwo-Chuan
;
電控工程研究所
The stabilization problem is considered in this study for a neural-network (NN) linearly interconnected system that consists of a number of NN models. First, a linear difference inclusion (LDI) state-space representation is established for the dynamics of each NN model. Then, based on the LDI state-space representation, a stability criterion in terms of Lyapunovs direct method is derived to guarantee the asymptotic stability of closed-loop NN linearly interconnected systems. Subsequently, according to this criterion and the decentralized control.scheme, a set of Takagi-Sugeno (T-S) fuzzy controllers is synthesized to stabilize the NN linearly interconnected system.. Finally, a numerical example with simulations is given to demonstrate the concepts discussed throughout this paper.
Decentralized stabilization of Nonlinear multiple time-delay interconnected systems via h-infinity fuzzy control
(2006)
Hsiao, Feng-Hsiag
;
Xu, Sheng-Dong
;
Lin, Chia-Yen
;
Chou, Yu-Jun
;
Chen, Yu-Ching
A robustness design of H-infinity fuzzy control is proposed in this paper to overcome the effect of modeling error between nonlinear multiple time-delay systems and fuzzy models. In terms of Lyapunov\'s direct method, a stability criterion is hence derived to guarantee the UUB (uniformly ultimately bounded) stability of nonlinear multiple time-delay interconnected systems with disturbances. Based on this criterion and the decentralized control scheme, a set of fuzzy controllers is then synthesized via the technique of parallel distributed compensation (PDC) to stabilize the nonlinear multiple time-delay interconnected systems and the H-infinity control performance is achieved in the mean time.
LQG optimal control of discrete stochastic systems under parametric and noise uncertainties
(2006-05-01)
Hsiao, Feng-Hsiag
;
Xu, Sheng-Dong
;
Wu, Shih-Lin
;
Lee, Gwo-Chuan
;
電控工程研究所
In this paper, the linear-quadratic-Gaussian (LQG) optimal control problem is considered and a robust minimax controller composed of the Kalman filter and the optimal regulator is synthesized to guarantee the asymptotic stability of the discrete time-delay systems under both parametric uncertainties and uncertain noise covariances. Designed procedures are finally elaborated with an illustrative example. (c) 2006 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Robust stabilization of fuzzy control for nonlinear multiple time-delay interconnected systems via neural-network-based approach
(2006)
Hsiao, Feng-Hsiag
;
Liang, Yew-Wen
;
Xu, Sheng-Dong
;
Lin, Chia-Yen
;
Tsai, Zhi-Ren
The stabilization problem is considered in this study for a nonlinear multiple time-delay large-scale (NMTDLS) system. First, the NN model is employed to approximate each subsystem. Then, an LDI state-space representation is established for the dynamics of each NN model. According to the LDI state-space representation, a robustness design of fuzzy control is proposed to overcome the effect of modeling errors between subsystems and NN models. Next, in terms of Lyapunov\'s direct method, a delay-dependent stability criterion is derived to guarantee the asymptotic stability of NMTDLS systems. Subsequently, a set of fuzzy controllers is synthesized to stabilize the NMTDLS system.
Robustness design of fuzzy control for nonlinear multiple time-delay large-scale systems via neural-network-based approach
(2008-02-01)
Hsiao, Feng-Hsiag
;
Xu, Sheng-Dong
;
Lin, Chia-Yen
;
Tsai, Zhi-Ren
;
電控工程研究所
The stabilization problem is considered in this correspondence for a nonlinear multiple time-delay large-scale system. First, the neural-network (NN) model is employed to approximate each subsystem. Then, a linear differential inclusion (LDI) state-space representation is established for the dynamics of each NN model. According to the LDI state-space representation, a robustness design of fuzzy control is proposed to overcome the effect of modeling errors between subsystems and NN models. Next, in terms of Lyapunov's direct method, a delay-dependent stability criterion is derived to guarantee the asymptotic stability of nonlinear multiple time-delay large-scale systems. Finally, based on this criterion and the decentralized control scheme, a set of fuzzy controllers is synthesized to stabilize the nonlinear multiple time-delay large-scale system.