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Design of Self-Organizing Intelligent Controller Using Fuzzy Neural Network

机译：基于模糊神经网络的自组织智能控制器设计

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摘要

In this paper, a self-organizing intelligent controller (SOIC) is proposed for a class of nonlinear systems. The basic idea of this study is to use a self-organizing fuzzy neural network to imitate control law directly, and then, appeal to obtain a compact structure of controller to further reduce the computational burden and enhance the control performance. First, an effective criterion, using the tracking performance and structure risk of controller, is developed to self-organize the control rules online for SOIC to improve the tracking performance. Second, the structure and parameters of SOIC are updated by an adaptive projection-type algorithm to reduce the heavy computational burden to speed up the control response. Third, the stability of SOIC is proved in the sense of Lyapunov and the guidelines for selecting the control parameters are given. Finally, the effectiveness of SOIC is illustrated with three nonlinear systems. It is shown that the proposed SOIC can achieve better control performance in comparison with some other control schemes.
机译：本文针对一类非线性系统提出了一种自组织智能控制器（SOIC）。这项研究的基本思想是使用自组织模糊神经网络直接模仿控制律，然后呼吁获得一种紧凑的控制器结构，以进一步减轻计算负担并提高控制性能。首先，利用控制器的跟踪性能和结构风险，制定了有效的准则，可以在线自组织SOIC的控制规则，以提高跟踪性能。其次，通过自适应投影型算法更新SOIC的结构和参数，以减轻繁重的计算负担，从而加快控制响应速度。第三，从Lyapunov的角度证明了SOIC的稳定性，并给出了选择控制参数的指南。最后，通过三个非线性系统说明了SOIC的有效性。结果表明，与其他控制方案相比，本文提出的SOIC可以实现更好的控制性能。

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  • 来源
    《IEEE Transactions on Fuzzy Systems》 |2018年第5期|3097-3111|共15页
  • 作者

    Hong-Gui Han; Xiao-Long Wu; Zheng Liu; Jun-Fei Qiao;

  • 作者单位

    Faculty of Information Technology and the Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China;

    Faculty of Information Technology and the Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China;

    Faculty of Information Technology and the Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China;

    Faculty of Information Technology and the Beijing Key Laboratory of Computational Intelligence and Intelligent System, Beijing University of Technology, Beijing, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Fuzzy neural networks; Fuzzy control; Nonlinear systems; Neurons; Stability analysis; Robustness; Control systems;

    机译：模糊神经网络;模糊控制;非线性系统;神经元;稳定性分析;鲁棒性;控制系统;

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