Variable structure control of unknown parameters DC servo systems using CMAC-based learning approach
Resource
American Control Conference, 2001. Proceedings of the 2001
Journal
American Control Conference, 2001. Proceedings of the 2001
Pages
-
Date Issued
2001-06
Date
2001-06
Author(s)
Lin, Wei-Song
Hung, Chin-Pao
DOI
N/A
Abstract
A CMAC-based controller with a compensating neural network and an update rule is proposed to design the variable structure control (VSC) of unknown parameters dc servo systems. By introducing a stabilizer controller and a CMAC neural network to construct the VSC control law, the new control scheme performs the equivalent control by a real-time learning algorithm. The stabilizer controller is designed by using Lyapunov stability theory and the updating rule of the CMAC weights is obtained by using the gradient descent method. Simulation results of a simplified robot link model demonstrate the effectiveness and robustness of the proposed controller.
SDGs
Type
journal article
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