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Hybrid Fuzzy PID Controller with Adaptive Genetic Algorithms for the Position Control of Linear Motors

Abstract
This thesis studies on the design of hybrid fuzzy PID controller via genetic algorithms and the position control of linear DC motors. Due to the high precision and high speed positioning ability, linear DC motors have been widely used in many fields. However, with the higher requirements of positioning accuracy, the effect of nonlinear friction becomes very significant. Because of the large difference between dynamic friction in macrodynamic region and static friction in microdynamic region, we design the two-stage controller for positioning in macrodynamic and microdynamic stage individually. In the macrodynamic stage, we use the hybrid fuzzy PID controller and finding the optimal membership functions and scaling factors of the controller via adaptive genetic algorithms to enhance performance of the system. A novel formula for calculating adaptive crossover and mutation rate is also presented. Since it is not easy to establish a precise static friction model in the microdynamic region, the relay feedback method is adopted to design PID controllers. Finally, through computer simulations and experiments, it is obviously that the performance of the proposed controllers is satisfactor

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0701103-224518
Date01 July 2003
CreatorsChen, Yi-Kuang
ContributorsHuey-Yang Horng, Ing-Rong Horng, Jyh-Horng Chou
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0701103-224518
Rightsunrestricted, Copyright information available at source archive

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