A New Fuzzy Inference Method for Symbolic Stability Analysis of Multigranular Intelligent Control System

2000 ◽  
Vol 12 (6) ◽  
pp. 664-674
Author(s):  
Hidehiro Yamamoto ◽  
◽  
Takeshi Furuhashi
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Fuzzy Control ◽  
Control Systems ◽  
Fuzzy Inference ◽  
Continuous System ◽  
Asymptotically Stable ◽  
Membership Functions ◽  
Symbolic System ◽  
Inference Method

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.

ANALYSIS OF A CLASS OF FUZZY CONTROLLERS

1994 ◽  
Vol 02 (03) ◽  
pp. 257-264 ◽  
Author(s):  
JOHN TAK KUEN KOO
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Theory ◽  
Nonlinear Control ◽  
Linear Function ◽  
Explicit Form ◽  
Membership Functions ◽  
Inference Method ◽  
Fuzzy Controllers ◽  
Nonlinear Control Theory

In this paper, a class of fuzzy controllers is considered. The controllers are constructed by applying product-max-COA(Center Of Area) inference method. The membership functions of the antecedence and the consequence are triangular and singelton in shape, respectively. The class of fuzzy controllers can be expressed by an explicit form, i.e. the sum of a linear function and some nonlinear terms. The explicit form of the class of controllers is generalized for multiple inputs. Therefore, by the use of the explicit form, the analysis of the fuzzy control system can be performed with the use of nonlinear control theory.

Research on Elevator Group Control Uncertainty

2014 ◽  
Vol 602-605 ◽  
pp. 874-877
Author(s):  
Dong Mei Yan ◽  
Li Liu
Keyword(s):  
Control System ◽  
Fuzzy Control ◽  
Control Theory ◽  
Simulation Model ◽  
Control Systems ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Group Control ◽  
Elevator Group Control

Uncertainties elevator group control systems are analyzed first in this paper according to the fuzzy control theory and characteristics of the elevator group control system. Then, simulation model of elevator group control system is built using fuzzy inference system with Matlab. Operation of elevator group control system based on fuzzy control system is shown by simulation.

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