MEMBERSHIP FUNCTIONS SHAPE AND ITS INFLUENCE ON THE STABILITY OF FUZZY CONTROL SYSTEMS

2000 ◽  
Vol 31 (4) ◽  
pp. 353-371 ◽  
Author(s):  
Petia Koprinkova
Author(s):  
LÁSZLÓ T. KÓCZY ◽  
MICHIO SUGENO

Fuzzy control systems have proved their applicability in many areas. Their user-friend-liness and transparency certainly belong to their main advantages, and these two enable developing and tuning such controllers easily, without knowing their exact mathematical description. Nevertheless, it is of interest to know, what mathematical functions hide behind a set of fuzzy rules and an inference machine. For practical purposes it is necessary to consider real, implementable fuzzy control systems with reasonably low computational complexity. This paper discusses the problem of what types of functions are generated by realistic fuzzy control systems. In the paper the explicit formulae of the transference functions for practically important special cases are determined, controllers having rules with triangular and trapezoidal membership functions, and crisp consequents. Here we restrict our investigations to rules with a single input.


2000 ◽  
Vol 12 (6) ◽  
pp. 664-674
Author(s):  
Hidehiro Yamamoto ◽  
◽  
Takeshi Furuhashi

Fuzzy inference has a multigranular architecture consisting of symbols and continuous values, and has worked well to incorporate experts' know-how into fuzzy controls. Stability analysis of fuzzy control systems is one of the main topics of fuzzy control. A recently proposed stability analysis method on the symbolic level opened the door to the design of stable fuzzy controller using symbols. However the validity of the stability analysis in the symbolic system is not guaranteed in the continuous system. To guarantee this validity, a nonseparate condition has been introduced. If the fuzzy control system is asymptotically stable in the symbolic system and the system satisfies the nonseparate condition, the continuous system is also asymptotically stable. However this condition is too conservative. The new condition called a relaxed nonseparate condition has been proposed and the class of control systems with guaranteed discretization has been expanded. However the relaxed condition has been applicable only to controf systems having symmetric membership functions. This paper presents a new fuzzy inference method that makes the relaxed condition applicable to fuzzy control systems with asymmetric membership functions. Simulations are done to demonstrate the effectiveness of the new fuzzy inference method. The proof of the expansion of the relaxed nonseparate condition is also given.


2011 ◽  
Vol 418-420 ◽  
pp. 1825-1828
Author(s):  
Ping Li ◽  
Chang Feng Yan ◽  
Ling Ke Zeng ◽  
Xiao Su Cheng

This article simulated fuzzy control system by using MATLAB and compared the normal fuzzy control system with the fuzzy control system which has an integrator. Further more, the influence of quantize factors, proportional factors and integral constants on system was studied. The simulation results show that static error always exists in normal fuzzy control systems and proportional factors influence the stability of the system greatly. Put an integrator into a fuzzy control system, and static error can be eliminated and the system stability can be improved. The conclusion of simulation and practical experience, use fuzzy control system with integrator in reality. It can get good results.


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