Auto-tuning of fuzzy logic controllers for self-regulating processes

Pao Yue-kong Library Electronic Theses Database

Auto-tuning of fuzzy logic controllers for self-regulating processes

 

Author: Chan, Kui-kee
Title: Auto-tuning of fuzzy logic controllers for self-regulating processes
Degree: M.Sc.
Year: 1999
Subject: Intelligent control systems
Fuzzy systems
Fuzzy logic
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Dept. of Electrical Engineering
Pages: 56 leaves : ill. ; 30 cm
Language: English
InnoPac Record: http://library.polyu.edu.hk/record=b1471948
URI: http://theses.lib.polyu.edu.hk/handle/200/1243
Abstract: In recent years, many complex industrial processes and domestic appliances have been successfully controlled by fuzzy logic controllers [1,2] and performances of fuzzy logic controllers sometimes outperform the conventional controllers. Unlike conventional process controller such as a PID controller, no rigorous mathematical model is required to design a good fuzzy logic controller and in many cases they can be implemented more easily. The aim of the project is to present an approach for auto-tuning of fuzzy logic controllers for unknown plant in which conventional method for formulation and design of fuzzy control strategies remain a trial and error exercise. The approach includes estimation of the parameter of the model and determination of the structure of the fuzzy logic controller. The idea is to present a simple and new approach to the autotuning of fuzzy logic controllers for unknown processes. Biased relay feedback test is applied to the unknown process and first order process with dead time model is fitted to the output response. The fuzzy logic controller for the control of the unknown process is then derived from the normalised fuzzy controller based on the fitted system gain, time constant and time delay. For dominant time delay process, Smith's predictor is included to compensate for the delay introduced in the feedback loop such that a more stable control loop is resulted. The fuzzy logic controller with delay compensation is then applied to different processes to demonstrate the effectiveness of the proposed scheme.

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