基于模糊神经网络算法的自适应后退位置控制系统

5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011) Pub Date : 2011-06-30 DOI:10.1109/DEST.2011.5936620

H. Kim, K. Park, Seock Joon Kim

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引用次数: 1

摘要

针对具有系统不确定性的伺服系统，研究了基于模糊神经网络算法的自适应后退位置控制系统。利用连续李雅普诺夫控制函数(LCF)的定义推导出该控制方案。此外，为了保证所提控制方案的稳定性，采用自适应规则更新fnn的连接权向量。通过计算机仿真，比较了基于fnn的自适应反步控制系统与标准反步控制系统的有效性。

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Adaptive back-stepping position control system with fuzzy neural networks algorithm

This paper deals with adaptive back-stepping position control system with FNNs(fuzzy neural networks) algorithm for servo system with system uncertainty. The proposed control scheme is induced from the result with the definition of continuative LCF(Lyapunov control functions). In addition, to guarantee the stability problem of the proposed control scheme, the connection weight vector of the FNNs is updated by adaptive rule. The effectiveness of the adaptive back-stepping control system with the FNNs was compared with that of the standard back-stepping control system through computer simulation.

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5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)

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