Output tracking of fractional-order nonlinear systems via TS-FCMAC

Tung-Sheng Chiang, Chian-Song Chiu
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Abstract

The purpose of article is to develop a general Takagi-Sugeno fuzzy cerebellar model articulation controller (TS-FCMAC) and to apply to the tracking controller of fractional-order nonlinear systems. In this paper, a novel TS-CMAC controller is developed in two cases: off-line and on-line learning. First, the off-line learning convergence of TS-FCMAC is analyzed and is confined to a least square error, when the learning rate approaches to zero as the iteration goes to infinity. The benefit is having high potential to functional learning by simpler network structure. Second, the on-line learning TS-FCMAC is designed to assure tracking control. Also, we apply the TS-CMAC to realize the ideal control law for fractional-order nonlinear systems and to achieve asymptotic stability. Finally, simulation results demonstrate the validity of the purposed control scheme.
基于TS-FCMAC的分数阶非线性系统输出跟踪
本文的目的是开发一种通用的Takagi-Sugeno模糊小脑模型关节控制器(TS-FCMAC),并将其应用于分数阶非线性系统的跟踪控制器。本文针对离线学习和在线学习两种情况,开发了一种新的TS-CMAC控制器。首先,分析了TS-FCMAC的离线学习收敛性,并将其限制在最小二乘误差范围内,当迭代趋于无穷时,学习率趋于零。其优点是网络结构简单,具有较高的功能学习潜力。其次,设计了在线学习的TS-FCMAC,以保证跟踪控制。应用TS-CMAC实现了分数阶非线性系统的理想控制律,并实现了系统的渐近稳定。最后,仿真结果验证了所设计控制方案的有效性。
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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