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Parameterization and Adaptive Control of Multivariable Noncanonical T--S Fuzzy Systems

机译:多变量非经典TS模糊系统的参数化与自适应控制

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摘要

This paper conducts a new study for adaptive Takagi–Sugeno (T–S) fuzzy approximation-based control of multi-input and multi-output (MIMO) noncanonical-form nonlinear systems. Canonical-form nonlinear systems have explicit relative degree structures, whose approximation models can be directly used to derive desired parameterized controllers. Noncanonical-form nonlinear systems usually do not have such a feature, nor do their approximation models, which are also in noncanonical forms. This paper shows that it is desirable to reparameterize noncanonical-form T–S fuzzy system models with smooth membership functions for adaptive control, and such system reparameterization can be realized using relative degrees, a concept yet to be studied for MIMO noncanonical-form T–S fuzzy systems. This paper develops an adaptive feedback linearization scheme for control of such general system models with uncertain parameters, by first deriving various relative degree structures and normal forms for such systems. Then, a reparameterization procedure is developed for such system models, based on which adaptive control designs are derived, with desired stability and tracking properties analyzed. A detailed example is presented with simulation results to show the new control design procedure and desired control system performance.
机译:本文对基于Takagi-Sugeno(TS)模糊逼近的多输入多输出(MIMO)非规范形式非线性系统的自适应控制进行了新的研究。规范形式的非线性系统具有显式的相对度结构,其近似模型可以直接用于导出所需的参数化控制器。非规范形式的非线性系统通常不具有这样的特征,其近似模型也不具有非规范形式。本文表明,需要对具有平滑隶属函数的非规范形式T–S模糊系统模型进行重新参数化以进行自适应控制,并且可以使用相对度来实现这种系统重新参数化,这是MIMO非规范形式T–S有待研究的概念S模糊系统。通过首先推导此类系统的各种相对度结构和范式,本文开发了一种自适应反馈线性化方案,用于控制具有不确定参数的此类一般系统模型。然后,针对此类系统模型开发了重新参数化程序,在此基础上得出自适应控制设计,并分析了所需的稳定性和跟踪特性。给出了带有仿真结果的详细示例,以显示新的控制设计程序和所需的控制系统性能。

著录项

  • 来源
    《IEEE Transactions on Fuzzy Systems》 |2017年第1期|156-171|共16页
  • 作者单位

    College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China;

    Department of Electrical and Computer Engineering, University of Virginia, Charlottesville, VA, USA;

    College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China;

    College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, 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 systems; Nonlinear systems; Adaptation models; Adaptive control; MIMO; Control systems;

    机译:模糊系统;非线性系统;适应模型;自适应控制;MIMO;控制系统;

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