Uncertain Fractional Order Chaotic Systems Tracking Design via Adaptive Hybrid Fuzzy Sliding Mode Control

Author:

Lin Tsung-Chih,Kuo Chia-Hao,Balas Valentina E.

Abstract

In this paper, in order to achieve tracking performance of uncertain fractional order chaotic systems an adaptive hybrid fuzzy controller is proposed. During the design procedure, a hybrid learning algorithm combining sliding mode control and Lyapunov stability criterion is adopted to tune the free parameters on line by output feedback control law and adaptive law. A weighting factor, which can be adjusted by the trade-off between plant knowledge and control knowledge, is adopted to sum together the control efforts from indirect adaptive fuzzy controller and direct adaptive fuzzy controller. To confirm effectiveness of the proposed control scheme, the fractional order chaotic response system is fully illustrated to track the trajectory generated from the fractional order chaotic drive system. The numerical results show that tracking error and control effort can be made smaller and the proposed hybrid intelligent control structure is more flexible during the design process.

Publisher

Agora University of Oradea

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Zadeh's Centenary;INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL;2021-01-17

2. On the Synchronization and Stabilization of fractional-order chaotic systems: Recent advances and future perspectives;Physica A: Statistical Mechanics and its Applications;2020-08

3. Designing of a Control Approach for Uncertain Fractional Order Systems with Indirect Adaptive Fuzzy Controller and Frational Order Sliding Mode;Journal of Control;2020-06-01

4. An Adaptive Interval Type-2 Fuzzy Sliding Mode Control Scheme for Fractional Chaotic Systems Synchronization With Chattering Elimination;Advanced Synchronization Control and Bifurcation of Chaotic Fractional-Order Systems;2018

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