Supervisory fuzzy neural network controller for slider-crank mechanism

Faa Jeng Lin, Rong Fong Fung, Hsin Hai Lin, Chih Ming Hong

Research output: Contribution to conferencePaperpeer-review

10 Scopus citations

Abstract

A supervisory fuzzy neural network (FNN) controller is proposed to control a nonlinear slider-crank mechanism in this study. The control system is composed of a permanent magnet (PM) synchronous servo motor drive coupled with a slider-crank mechanism and a supervisory FNN position controller. The supervisory FNN controller comprises a sliding mode FNN controller and a supervisory controller. The sliding mode FNN controller combines the advantages of the sliding mode control with robust characteristics and the FNN with on-line learning ability. The supervisory controller is designed to stabilize the system states around a defined bound region. The theoretical and stability analyses of the supervisory FNN controller are discussed in detail. Simulation and experimental results are provided to show that the proposed control system is robust with regard to plant parameter variations and external load disturbance.

Original languageEnglish
Pages1710-1715
Number of pages6
StatePublished - 1999
EventProceedings of the 1999 IEEE International Conference on Control Applications (CCA) and IEEE International Symposium on Computer Aided Control System Design (CACSD) - Kohala Coast, HI, USA
Duration: 22 Aug 199927 Aug 1999

Conference

ConferenceProceedings of the 1999 IEEE International Conference on Control Applications (CCA) and IEEE International Symposium on Computer Aided Control System Design (CACSD)
CityKohala Coast, HI, USA
Period22/08/9927/08/99

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