DocumentCode :
3251910
Title :
Self-organizing model based expert controller
Author :
Batur, C. ; Kasparian, V.
Author_Institution :
Dept. of Mech. Eng., Akron Univ., OH, USA
fYear :
1989
fDate :
0-0 1989
Firstpage :
411
Lastpage :
414
Abstract :
A self-tuning expert fuzzy controller is developed and applied in real time to a process control problem. The knowledge base consists of rules describing the control law in terms of the process error and the resulting control action. Conditions and conclusions of each rule are fuzzy variables which are described through their continuous membership curves. The inference engine used is the backward chaining process of the Prolog language. To implement the self-tuning property, the membership curve of the controller output is changed according to an error-based performance index. A control supervisor makes this tuning decision as a function of either past or predicted future set-point errors of the control system. If the current process model is considered reliable, then the decision is based on the predicted set-point error. The feasibility of this self-tuning expert controller is demonstrated on the speed control problem for a DC motor load system.<>
Keywords :
control system synthesis; controllers; inference mechanisms; self-adjusting systems; velocity control; DC motor load system; Prolog language; error-based performance index; inference engine; knowledge base; process control problem; process error; self organising model based expert controller; self-tuning expert fuzzy controller; speed control problem; Inference mechanisms; Velocity control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems Engineering, 1989., IEEE International Conference on
Conference_Location :
Fairborn, OH, USA
Type :
conf
DOI :
10.1109/ICSYSE.1989.48704
Filename :
48704
Link To Document :
بازگشت