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Hybrid Fuzzy PID Controller with Adaptive Genetic Algorithms for the Position Control and Improvement of Magnetic Suspension System

Magnetic suspension systems are highly nonlinear and essentially unstable systems. In this thesis, we utilize a phase-lead controller operating in the inner loop to stabilize the magnetic suspension system at first. Furthermore, we design a fuzzy PID controller operating in the outer loop to overcome the nonlinearity and to improve the system¡¦s performances.
Because of setting the parameters in traditional fuzzy PID is a long-winded trial and error, so we adopt non-binary modified adaptive genetic algorithms to help us finding the parameters of fuzzy PID controller. As to the experimental implementation, we set two situations in our experiment test: (1) we utilize fuzzy PID controller with initial voltage to test the positions control, and eliminate the extra disturbance. And, (2) we utilize fuzzy PID controller without initial voltage to control the position of suspension object.
For the experimental results, we obtain that the designed fuzzy PID controller not only increases the system¡¦s operating range, but also positions accurately and rapidly, and it meanwhile can eliminate the extra disturbance.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0624104-182807
Date24 June 2004
CreatorsHuang, Jiun-kuei
ContributorsIng-Rong Horng, Chien-Hsiang Chao, Tsung-Chuan Huang
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-0624104-182807
Rightswithheld, Copyright information available at source archive

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