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Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints

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  • Changhui Wang
  • Mei Liang
  • Yongsheng Chai

Abstract

An adaptive backstepping control scheme for a class of incommensurate fractional order uncertain nonlinear multiple-input multiple-output (MIMO) systems subjected to constraints is discussed in this paper, which ensures the convergence of tracking errors even with dead-zone and saturation nonlinearities in the controller input. Combined with backstepping and adaptive technique, the unknown nonlinear uncertainties are approximated by the radial basis function neural network (RBF NN) in each step of the backstepping procedure. Frequency distributed model of a fractional integrator and Lyapunov stability theory are used for ensuring asymptotic stability of the overall closed-loop system under input dead-zone and saturation. Moreover, the parameter update laws with incommensurate fractional order are used in the controller to compensate unknown nonlinearities. Two simulation results are presented at the end to ensure the efficacy of the proposed scheme.

Suggested Citation

  • Changhui Wang & Mei Liang & Yongsheng Chai, 2019. "Adaptive Neural Network Control of a Class of Fractional Order Uncertain Nonlinear MIMO Systems with Input Constraints," Complexity, Hindawi, vol. 2019, pages 1-15, November.
    • Handle: RePEc:hin:complx:1410278
    DOI: 10.1155/2019/1410278
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    References listed on IDEAS

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    1. Shiyun Shen & Wenjing Li & Wei Zhu, 2017. "Consensus of Fractional-Order Multiagent Systems with Double Integrator under Switching Topologies," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-7, August.
    2. Chunde Yang & Wenjing Li & Wei Zhu, 2017. "Consensus Analysis of Fractional-Order Multiagent Systems with Double-Integrator," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-8, January.
    3. Baoyu Huo & Shaocheng Tong & Yongming Li, 2013. "Adaptive fuzzy fault-tolerant output feedback control of uncertain nonlinear systems with actuator faults," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(12), pages 2365-2376.
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