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.
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