Hydraulic Servocylinder Position Control Using a Hybrid Neurofuzzy Controller

Article type: Research Article

Authors: Shih, Ming-Chang | Lee, Kuo-Chan

Affiliations: Department of Mechanical Engineering, National Cheng-Kung University, Tainan, Taiwan 70101, Republic of China

Abstract: The purpose of this article is to design a neurofuzzy controller with a hybrid learning algorithm and to control the position of a hydraulic servocylinder with an IBM compatible microcomputer. The structure of the neurofuzzy controller is based on the bell-shaped membership function and the Mamdani fuzzy reasoning rules. According to the training data and the hybrid neural network learning, the minimum fuzzy reasoning rules and the optimized membership function can be found automatically. The effects of different design parameters and the load disturbance are also studied experimentally.

DOI: 10.3233/IFS-1996-4302

Journal: Journal of Intelligent and Fuzzy Systems, vol. 4, no. 3, pp. 193-206, 1996