The H∞ design of SOS-based fuzzy controller for synchronization of chaotic systems

Author(s):  
Gwo-Ruey Yu ◽  
Chih-Heng Chang
Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Bo Wang ◽  
L. L. Chen

This paper concerns the problem on the fuzzy synchronization for a kind of disturbed memristive chaotic system. First, based on fuzzy theory, the fuzzy model for a memristive chaotic system is presented; next, based on H-infinity technique, a multidimensional fuzzy controller and a single-dimensional fuzzy controller are designed to realize the synchronization of master-slave chaotic systems with disturbances. Finally, some typical examples are included to illuminate the correctness of the given control method.


Author(s):  
FENG-HSIAG HSIAO ◽  
WEI-LING CHIANG ◽  
CHENG-WU CHEN ◽  
SHENG-DONG XU ◽  
SHIH-LIN WU

A robustness design of fuzzy control via model-based approach is proposed in this paper to overcome the effect of approximation error between nonlinear system and Takagi-Sugeno (T-S) fuzzy model. T-S fuzz model is used to model the resonant and chaotic systems and the parallel distributed compensation (PDC) is employed to determine structures of fuzzy controllers. Linear matrix inequality (LMI) based design problems are utilized to find common definite matrices P and feedback gains K satisfying stability conditions derived in terms of Lyapunov direct method. Finally, the effectiveness and the feasibility of the proposed controller design method is demonstrated through numerical simulations on the chaotic and resonant systems.


2012 ◽  
Vol 524-527 ◽  
pp. 3809-3814 ◽  
Author(s):  
Xiao Hua Wang ◽  
Dun Ao ◽  
Zhong Qiang Wu

We consider the synchronization problem of chaotic systems with uncertainties. We apply the fuzzy method to solve this problem, and the parameters of membership function are optimized by genetic algorithm, so that we can get the appropriate values for those parameters, and improve the ability of fuzzy controller. We carry out the simulations of synchronizing Henon chaotic systems with uncertainties, and the results show the effectiveness of this method.


Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo ◽  
Valentina E. Balas

In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.


2012 ◽  
Vol 1 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Tsung-Chih Lin ◽  
Chia-Hao Kuo

This paper presents an adaptive hybrid fuzzy controller to achieve prescribed tracking performance of fractional order chaotic systems. Depending on plant knowledge and control knowledge, a weighting factor can be adjusted by combining the indirect adaptive fuzzy control effort and the direct fuzzy adaptive control effort. Nonlinear fractional order chaotic response system is fully demonstrated to track the trajectory generated from fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control scheme is more flexible during the design process.


2014 ◽  
Vol 644-650 ◽  
pp. 2514-2521
Author(s):  
Juan Meng ◽  
Hai Du ◽  
Xing Yuan Wang

In this paper, a new fuzzy model-based adaptive approach for synchronization of chaotic systems with unknown parameters. Theoretical analysis based on Lyapunov stability theory is provided to verify its feasibility. Takagi-Sugeno (T-S) fuzzy model is employed to express the chaotic systems. Based on this model, an adaptive fuzzy controller and the parameters update law are developed. With the proposed scheme, parameters identification and synchronization of identical or nonidentical chaotic systems can be achieved simultaneously. Numerical simulations further demonstrate the effectiveness of the proposed scheme.


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