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首页> 外文期刊>Journal of the Franklin Institute >Finite-time adaptive neural control and almost disturbance decoupling for disturbed MIMO non-strict-feedback nonlinear systems
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Finite-time adaptive neural control and almost disturbance decoupling for disturbed MIMO non-strict-feedback nonlinear systems

机译：有限时间的自适应神经控制，几乎干扰解耦因而扰动MIMO非严格反馈非线性系统

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This paper investigates the finite-time adaptive neural control and almost disturbance decoupling problems for multi-input/multi-output (MIMO) nonlinear systems with disturbances and non-strict-feedback structure. In the design procedure of the adaptive controller, neural networks are employed to estimate the unknown nonlinearities and Young's inequality is utilized to cope with the disturbance terms derived from all subsystems. In order to characterize the disturbance attenuation performance of finite-time adaptive control, a criterion named finite-time almost disturbance decoupling is first developed. Under this criterion, an adaptive neural controller is designed via the backstepping method and the appropriate selection of Lyapunov function. It is revealed that the proposed controller can guarantee all variables of the closed-loop system are bounded, and the performance of finite-time almost disturbance decoupling is realized. Finally, a practical example is employed to validate the effectiveness of the designed controller. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译：本文调查了具有干扰和非严格反馈结构的多输入/多输出（MIMO）非线性系统的有限时间自适应神经控制和几乎干扰解耦问题。在自适应控制器的设计过程中，神经网络被用于估计未知的非线性，并且杨氏不等式用于应对源自所有子系统的干扰术语。为了表征有限时间自适应控制的扰动衰减性能，首先开发出一个名为Unitipt-Time几乎干扰去耦的标准。 Under this criterion, an adaptive neural controller is designed via the backstepping method and the appropriate selection of Lyapunov function.据透露，所提出的控制器可以保证闭环系统的所有变量是有界的，并且实现了有限时间几乎干扰去耦的性能。最后，采用实际例子来验证设计控制器的有效性。 （c）2019年富兰克林学院。 elsevier有限公司出版。保留所有权利。

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    《Journal of the Franklin Institute》 |2020年第16期|11750-11772|共23页
  • 作者

    Jiang Kun; Wang Xiaomei; Niu Ben; Wang Zhenhua; Li Junqing; Duan Peiyong; Yang Dong;

  • 作者单位

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China;

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China;

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China;

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China;

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China|Liaocheng Univ Sch Comp Liaocheng 252059 Shandong Peoples R China;

    Shandong Normal Univ Sch Informat Sci & Engn Jinan 250014 Peoples R China;

    Qufu Normal Univ Sch Engn Rizhao 276826 Peoples R China;

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