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PID Learning Controller for Multivariable System with Dynamic Friction  

Chung, Byeong-Mook (영남대학교 공과대학 기계공학부)
Publication Information
Journal of the Korean Society for Precision Engineering / v.24, no.12, 2007 , pp. 57-64 More about this Journal
Abstract
There have been many researches for optimal controllers in multivariable systems, and they generally use accurate linear models of the plant dynamics. Real systems, however, contain nonlinearities and high-order dynamics that may be difficult to model using conventional techniques. Therefore, it is necessary a PID gain tuning method without explicit modeling for the multivariable plant dynamics. The PID tuning method utilizes the sign of Jacobian and gradient descent techniques to iteratively reduce the error-related objective function. This paper, especially, focuses on the role of I-controller when there is a steady state error. However, it is not easy to tune I-gain unlike P- and D-gain because I-controller is mainly operated in the steady state. Simulations for an overhead crane system with dynamic friction show that the proposed PID-LC algorithm improves controller performance, even in the steady state error.
Keywords
PID (Proportional, Integral, and Derivative); LC (Learning Control); Multivariable System; Dynamic Friction; Overhead Crane;
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Times Cited By KSCI : 2  (Citation Analysis)
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