scholarly journals Takagi-Sugeno Fuzzy Control Based on Robust Stability Specifications

10.5772/13623 ◽  
2011 ◽  
Author(s):  
Joabe A. ◽  
Ginalber L. O. Serr
Keyword(s):  
Fuzzy Control ◽  
Robust Stability ◽  
Takagi Sugeno

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

2021 ◽  
Author(s):  
Cheung-Chieh Ku ◽  
Wen-Jer Chang ◽  
Ming-Hsuan Tsai ◽  
Yi-Chen Lee
Keyword(s):  
Fuzzy Control ◽  
Fuzzy Systems ◽  
Takagi Sugeno

A DELAY-DEPENDENT APPROACH TO ROBUST TAKAGI–SUGENO FUZZY CONTROL OF UNCERTAIN RECURRENT NEURAL NETWORKS WITH MIXED INTERVAL TIME-VARYING DELAYS

2011 ◽  
Vol 20 (08) ◽  
pp. 1571-1589 ◽  
Author(s):  
K. H. TSENG ◽  
J. S. H. TSAI ◽  
C. Y. LU
Keyword(s):  
Fuzzy Control ◽  
Time Delays ◽  
Sufficient Conditions ◽  
Upper And Lower Bounds ◽  
Linear Matrix ◽  
Uncertain Parameters ◽  
Time Varying ◽  
Interval Time ◽  
Delay Dependent ◽  
Takagi Sugeno

This paper deals with the problem of globally delay-dependent robust stabilization for Takagi–Sugeno (T–S) fuzzy neural network with time delays and uncertain parameters. The time delays comprise discrete and distributed interval time-varying delays and the uncertain parameters are norm-bounded. Based on Lyapunov–Krasovskii functional approach and linear matrix inequality technique, delay-dependent sufficient conditions are derived for ensuring the exponential stability for the closed-loop fuzzy control system. An important feature of the result is that all the stability conditions are dependent on the upper and lower bounds of the delays, which is made possible by using the proposed techniques for achieving delay dependence. Another feature of the results lies in that involves fewer matrix variables. Two illustrative examples are exploited in order to illustrate the effectiveness of the proposed design methods.

Comments on “Takagi–Sugeno fuzzy control for a wide class of fractional-order chaotic systems with uncertain parameters via linear matrix inequality”

2019 ◽  
Vol 26 (9-10) ◽  
pp. 643-645
Author(s):  
Xuefeng Zhang
Keyword(s):  
Fuzzy Control ◽  
Linear Matrix Inequality ◽  
Fractional Order ◽  
Wide Class ◽  
Chaotic Systems ◽  
Sufficient Conditions ◽  
Linear Matrix ◽  
Uncertain Parameters ◽  
Matrix Inequality ◽  
Takagi Sugeno

This article shows that sufficient conditions of Theorems 1–3 and the conclusions of Lemmas 1–2 for Takasi–Sugeno fuzzy model–based fractional order systems in the study “Takagi–Sugeno fuzzy control for a wide class of fractional order chaotic systems with uncertain parameters via linear matrix inequality” do not hold as asserted by the authors. The reason analysis is discussed in detail. Counterexamples are given to validate the conclusion.

scholarly journals Enhancing vehicle suspension system control performance based on the improved extension control

2018 ◽  
Vol 10 (7) ◽  
pp. 168781401877386 ◽  
Author(s):  
Hongbo Wang
Keyword(s):  
Fuzzy Control ◽  
System Performance ◽  
Ride Comfort ◽  
Control Method ◽  
Domain Boundary ◽  
Suspension System ◽  
Vehicle Suspension ◽  
Classical Domain ◽  
Vehicle Suspension System ◽  
Takagi Sugeno

Vehicle suspension system is the key part in vehicle chassis, which has influence on the vehicle ride comfort, handling stability, and security. The extension control, which is not constrained by common control method, could further improve the suspension system performance. The 7 degree-of-freedom suspension model is built. The extension controller is designed according to the function differences. In different extension set domains according to the correlation function, the corresponding control strategy is designed to ensure the suspension system obtains optimal performance in the classical domain and expands the controllable range outside the classical domain as large as possible. By adopting game theory, the domain is optimally divided, and the domain boundary control jump is smoothed by introducing Takagi–Sugeno–Kang fuzzy control into the extension control. Through the simulation and results comparison, it is demonstrated that the extension control could further improve the vehicle ride comfort than the optimal control and the extension control ability can be further promoted through domain game and Takagi–Sugeno–Kang fuzzy control. The analysis of the influence of the extension controller parameter varieties on suspension system performance shows that the error-weighted coefficient and control coefficient have significant effect to the suspension system performance.

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