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[[alternative]]A Study of Improving the accuracy of Fuzzy CMAC using Residual Theory Design and Its Application

By [[author]]曹建和, [[author]]Chien Ho Tsao, 曹建和 and Chien Ho Tsao

Abstract

[[abstract]]For traditional industry process control, the PID controller is the most commonly used. Although the rule of PID control is simple, the main defect of PID control is that the individual gain parameters cannot be automatically adjusted when the controlled system changes. To improve this, the Ziegler-Nichols parameter setting method, the Fuzzy logic parameter setting method, and the Artificial Intelligence control theory are developed hence. The features of these methods are to imitate artificial intelligence, which can solve the problems of complexity, indetermination and nonlinear of traditional control technique, without precise mathematics model needed. The receptive field function of conventional CMAC uses the basic function of binary box, which cannot store the differential information between input and output. Also, due to the approximate property of CMAC and computer round-off error, it limits the adjustment of the system parameter and the accuracy of practical application. So, this paper presents a new index rule, which fully connects the addressing scheme and receptive field function, called RFCMAC. It not only can keep the advantages of CMAC, but also can store the differential information between input and output, which is able to auto-adjust the system parameter and improve the accuracy. Finally, to demonstrate its practical control system capability and performance of improving the accuracy, I apply the proposed structure in the position of tracking of Linear Piezoelectric Ceramic Motor (LPCM). From the experimental results, any one input of the reference model of step function or sine wave will do, the position tracking response of moving table can be closely follow the reference model compares RFCMAC with PI structure and has been successfully implemented to control the position tracking of LPCM to achieve improvement the accuracy.

Topics: PID控制器, 模糊控制, 小腦模型控制器, 殘差修正之模糊小腦模型控制器, 線性壓電陶瓷馬達, PID controller, Fuzzy control, CMAC, RFCMAC, LPCM, [[classification]]53
Year: 2010
OAI identifier: oai:ir.lib.ntnu.edu.tw:309250000Q/6590
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