Discrete Fuzzy Controller Design for Achieving Common State Covariance Assignment

2004 ◽  
Vol 126 (3) ◽  
pp. 627-632 ◽  
Author(s):  
Wen-Jer Chang ◽  
Chong-Cheng Shing
Keyword(s):  
Feedback Control ◽  
Covariance Matrix ◽  
Output Feedback ◽  
Fuzzy Systems ◽  
Fuzzy Controller ◽  
Controller Design ◽  
Fuzzy Model ◽  
Output Feedback Control ◽  
Control Approach ◽  
Takagi Sugeno

In this paper, a method is developed to find the output feedback fuzzy controllers for assigning a common state covariance matrix of discrete Takagi–Sugeno (T–S) fuzzy systems. The fuzzy control approach developed in this paper is based on the concept of Parallel Distributed Compensation (PDC). For each rule of the discrete T–S fuzzy model, it shows how to parameterize the static linear output feedback control gains to achieve a common state covariance matrix for each subsystem. Finally, a numerical example is provided to verify the effects of the proposed method.

Robust H∞ Takagi–Sugeno fuzzy output-feedback control for differential speed steering vehicles

2020 ◽  
Vol 234 (12) ◽  
pp. 2822-2835 ◽  
Author(s):  
Paul Oke ◽  
Sing Kiong Nguang
Keyword(s):  
Feedback Control ◽  
Lyapunov Function ◽  
Electric Vehicles ◽  
Output Feedback ◽  
Controller Design ◽  
Output Feedback Control ◽  
Operating Conditions ◽  
Fuzzy Lyapunov Function ◽  
Takagi Sugeno ◽  
Differential Speed

This paper studied the modelling and control of four-wheel independently driven electric vehicles using differential speed steering. The Takagi–Sugeno fuzzy modelling approach represents the nonlinearities of the four-wheel independently driven electric vehicle state variables in several system models. The proposed controller design is a robust Takagi–Sugeno fuzzy output-feedback control based on a fuzzy Lyapunov function approach. More precisely, the Lyapunov function is chosen to be dependent on the membership functions. Sufficient conditions for the existence of the robust Takagi–Sugeno fuzzy controller are given in terms of linear matrix inequality constraints. The designed parameters are tested by simulating the four-wheel independently driven electric vehicles under varying operating conditions. The simulation results underscore the robustness and disturbance rejection importance of the proposed controller, which is then contrasted to better highlight the improved performance of the proposed approach over a fixed robust controller design.

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