A self-organizing fuzzy CMAC for sliding mode control

Kao-Shing Hwang, Ching-Shun Lin
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引用次数: 1

Abstract

A neuro-fuzzy system is proposed to tackle physical learning control problems in this paper. The control scheme is composed of two elements. The first element, the fuzzy sliding mode controller, is used to drive the state variables to a specific switching hyperplane or a desired trajectory. The second one is developed based on the concept of the fuzzy cerebellar model articulation controller (FCMAC) and adaptive heuristic critic (AHC). Both compose a forward compensator to reduce the chattering effect or cancel the influence of system uncertainties. Simulations on chattering reduction is given to illustrate the performance and applicability of the proposed control scheme.
滑模控制的自组织模糊CMAC
本文提出了一种神经模糊系统来解决物理学习控制问题。控制方案由两个部分组成。第一个单元是模糊滑模控制器,用于将状态变量驱动到特定的切换超平面或期望的轨迹。第二种是基于模糊小脑模型发音控制器(FCMAC)和自适应启发式批评(AHC)的概念发展起来的。两者都组成正向补偿器来减小抖振效应或消除系统不确定性的影响。通过对颤振抑制的仿真,验证了该控制方案的性能和适用性。
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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