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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46991

Title: Adaptive output recurrent cerebellar model articulation controller for nonlinear system control
Authors: Chih-Hui Chiu
Contributors: 國立臺灣海洋大學:通訊科學系
Keywords: Adaptive output recurrent
Gradient descent method
Optimal learning-rates
Model free control
Date: 2010
Issue Date: 2018-06-26T08:03:56Z
Publisher: Soft Computing
Abstract: Abstract: In this study, an adaptive output recurrent cerebellar model articulation controller (AORCMAC) is investigated for a nonlinear system. The proposed AORCMAC has superior capability to the conventional cerebellar model articulation controller in efficient learning mechanism and dynamic response. The dynamic gradient descent method is adopted to online adjust the AORCMAC parameters. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of AORCMAC so that the stability of the system can be guaranteed. Furthermore, the variable optimal learning-rates are derived to achieve the best convergence of tracking error. Finally, the effectiveness of the proposed control system is verified by the several simulation and experimental results. Those results show that the favorable performance can be obtained by using the proposed AORCMAC.
Relation: 14(6) pp.627–638
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/46991
Appears in Collections:[通訊與導航工程學系] 期刊論文

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