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

机译:通过TS-FCMAC输出分数级非线性系统的输出跟踪

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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.
机译:物品的目的是开发一般的Takagi-Sugeno模糊小脑模型铰接控制器(TS-FCMAC),并适用于分数级非线性系统的跟踪控制器。 本文在两种情况下开发了一种新颖的TS-CMAC控制器:离线和在线学习。 首先,分析TS-FCMAC的离线学习收敛,并且当迭代到无穷大时,学习速率接近零时,将被限制为最小二乘误差。 通过更简单的网络结构,利益具有很高的功能学习。 其次,在线学习TS-FCMAC旨在确保跟踪控制。 此外,我们应用TS-CMAC实现分数级非线性系统的理想控制法,实现渐近稳定性。 最后,仿真结果表明了所用控制方案的有效性。

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