Decentralized Stabilization of Nonlinear Multiple Time-Delay Interconnected Systems via H-infinity Fuzzy Control

2006 ◽  
Author(s):  
Feng-Hsiag Hsiao ◽  
Sheng-Dong Xu ◽  
Chia-Yen Lin ◽  
Yu-Jun Chou ◽  
Yu-Ching Chen ◽  
...  
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Interconnected Systems ◽  
Multiple Time ◽  
H Infinity ◽  
Decentralized Stabilization

DECENTRALIZED STABILIZATION OF H FUZZY CONTROL FOR NONLINEAR MULTIPLE TIME-DELAY INTERCONNECTED SYSTEMS

2008 ◽  
Vol 9 (1) ◽  
pp. 104-110 ◽  
Author(s):  
Feng-Hsiag Hsiao ◽  
Sheng-Dong Xu ◽  
Chia-Yen Lin ◽  
Yu-Jun Chou ◽  
Yu-Ching Chen
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Interconnected Systems ◽  
Multiple Time ◽  
Decentralized Stabilization

Robust stabilization of nonlinear multiple time-delay large-scale systems via decentralized fuzzy control

2005 ◽  
Vol 13 (1) ◽  
pp. 152-163 ◽  
Author(s):  
Feng-Hsiag Hsiao ◽  
Jung-Dong Hwang ◽  
Cheng-Wu Chen ◽  
Zhi-Ren Tsai
Keyword(s):  
Time Delay ◽  
Fuzzy Control ◽  
Large Scale ◽  
Robust Stabilization ◽  
Multiple Time ◽  
Large Scale Systems

Optimal H∞ Fuzzy Control for Nonlinear Interconnected Systems via Genetic Algorithm

2013 ◽  
Vol 459 ◽  
pp. 256-261
Author(s):  
Feng Hsiag Hsiao ◽  
Chien Yu Liu
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Control ◽  
Direct Method ◽  
Random Search ◽  
Disturbance Attenuation ◽  
Interconnected Systems ◽  
Space Representation ◽  
Multiple Time ◽  
Interconnected System ◽  
Fuzzy Controllers

This paper presents an effective approach for stabilizing nonlinear multiple time-delay (NMTD) interconnected systems via a composite of genetic algorithm (GA) and fuzzy controllers. First, a neural-network (NN) model is employed to approximate each subsystem with multiple time delays. Then, the dynamics of the NN model is converted into a linear differential inclusion (LDI) state-space representation. Next, in terms of Lyapunov's direct method, a delay-dependent stability criterion is derived to guarantee the exponential stability of the NMTD interconnected system. Subsequently, the stability condition of this criterion is reformulated into a linear matrix inequality (LMI). Due to the capability of GA in a random search for global optimization, the lower and upper bounds of the search space can be set so that the GA will seek better feedback gains of fuzzy controllers in order to stabilize more quickly the NMTD interconnected system based on the feedback gains via LMI-based approach. According to the Improved genetic algorithm (IGA), which is demonstrated to have better performance than that of a traditional GA, a robustness design of fuzzy control is synthesized not only to stabilize the NMTD interconnected system but also to achieve optimal H performance by minimizing the disturbance attenuation level.

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