Abstract

This paper discusses adaptive control method used in high performance servo system based on Cerebellar Model Articulation Controller(CMAC). It analyzes the uncertain and nonlinear factors of the servo system, studies the modeling method using the frequency property of the system, and then uses an additional item to instead of the non-modeling factor. In the proposed control scheme, the CMAC controller is able to learn the unknown model dynamics, parameter variation and disturbance of the system on line. The model reference adaptive control (MRAC) scheme is used to give better solutions with online adaptation. It contemporarily improved the conception mapping algorithm of the Cerebellar Model Articulation Controller Neural Network(CMACNN), which gave a determined expression of the physical memory size and designed a physical memory address function. Experiment results verify that the proposed strategy can achieve high tracking precision for real-time position close-loop servo system.

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