Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.663452
Title: Robust control with fuzzy logic algorithms
Author: Wang, Jian Zhou
Awarding Body: University of Edinburgh
Current Institution: University of Edinburgh
Date of Award: 1997
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Abstract:
This thesis presents the results of an investigation of the robustness of the widely used Mandani-type fuzzy logic control systems under a wide variation of parameters of the controlled process. The measurements of the dynamic performance and system robustness of a control system were firstly defined from the engineering point of view, and the concepts of the robust space and the robustness index were introduced. The robustness of the FLC systems was investigated by analyzing the structure of the fuzzy rule base and membership functions of the input-output variables. Based on the close relation of the fuzzy rule base and the system dynamic trajectory on the phase plane, a switching line method is introduced to qualitatively analyze the dynamic performance of the SISO FLC systems. This switching line method enables the qualitative prediction of the shape and position of the robust space of the FLC controlled first order processes and second order processes. The effects of FLC parameters on system robustness were also investigated. The movements of the position and the shape of the switching line with the variation of the controller parameters were analyzed, and its relation with the system performance was reported. Three methods were proposed to improve the robustness of the FLC system. The first design method proposed was based on the switching line characteristics of the FLC system. The second method, called phase advanced FLC, was introduced to handle the control of high order processes with fuzzy algorithms. The third method was an evolutionary method based on the genetic algorithm which was used to automatically design a robust fuzzy control system, assuming the availability of the controlled process model.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.663452  DOI: Not available
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