Observer-based proportional derivative fuzzy control for singular Takagi-Sugeno fuzzy systems

Author(s):  
Cheung-Chieh Ku ◽  
Wen-Jer Chang ◽  
Ming-Hsuan Tsai ◽  
Yi-Chen Lee
2011 ◽  
Vol 2011 ◽  
pp. 1-21 ◽  
Author(s):  
Leonardo Amaral Mozelli ◽  
Reinaldo Martinez Palhares

New analysis and control design conditions of discrete-time fuzzy systems are proposed. Using fuzzy Lyapunov's functions and introducing slack variables, less conservative conditions are obtained. The controller guarantees system stabilization and performance. Numerical tests and a practical experiment in Chua's circuit are presented to show the effectiveness.


2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Sunjie Zhang ◽  
Zidong Wang ◽  
Jun Hu ◽  
Jinling Liang ◽  
Fuad E. Alsaadi

The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.


Author(s):  
Yang Liu ◽  
Xiaojun Ban ◽  
Fen Wu ◽  
H. K. Lam

Due to the universal approximation capability of Takagi–Sugeno (T–S) fuzzy models for nonlinear dynamics, many control issues have been investigated based on fuzzy control theory. In this paper, a transformation procedure is proposed to convert fuzzy models into linear fractional transformation (LFT) models. Then, T–S fuzzy systems can be regarded as a special case of linear parameter-varying (LPV) systems which proved useful for nonlinear control problems. The newly established connection between T–S fuzzy models and LPV models provides a new perspective of the control problems for T–S fuzzy systems and facilitates the fuzzy control designs. Specifically, an output feedback gain-scheduling control design approach for T–S fuzzy systems is presented to ensure globally asymptotical stability and optimize H∞ performance of the closed-loop systems. The control synthesis problem is cast as a convex optimization problem in terms of linear matrix inequalities (LMIs). Two examples have been used to illustrate the efficiency of the proposed method.


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