一类非线性动态系统的CMAC网络学习控制的收敛性

Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014) Pub Date : 1900-01-01 DOI:10.1109/ISIC.1999.796639

Hui Liu, Danwei W. Wang

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引用次数: 2

摘要

由于神经网络闭环系统的高度非线性特性，使得其收敛性分析非常困难。本文采用小脑模型发音控制器(CMAC)作为迭代学习控制器，基于迭代学习控制理论分析了闭环系统的收敛性。仿真结果验证了分析的正确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Convergence of CMAC network learning control for a class of nonlinear dynamic system

Due to the high nonlinear property, the convergence of neural network based closed-loop system are very difficult to analyze. In the paper, we adopt cerebellar model articulation controller (CMAC) as an iterative learning controller, the convergence of the closed-loop system is analyzed based on the iterative learning control theory. Simulation results verify the analysis.

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来源期刊

Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)

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