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State feedback control of interval type-2 T S model based uncertain stochastic systems with unmatched premises

机译:区间不匹配的不确定区间2区间TS模型的状态反馈控制

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摘要

This paper is concerned with the state feedback control for interval type-2 (IT2) uncertain Ito stochastic fuzzy systems with a multidimensional Wiener process and unmatched premises. The uncertainties are of linear fractional form, and appear not only in the membership functions but also in the parametric matrices of the systems. The fuzzy basis functions of the controllers to be designed are different from those of the IT2 fuzzy model. Since stochastic perturbations and unmatched premises as well as parametric uncertainties are involved in the underlying systems, the stabilization problem becomes more complicated and challenging than that for deterministic systems. Facilitating by space decomposition, the lower and upper membership functions (LUMFs) can be locally represented in terms of the convex combinations of some local basis functions whose coefficients can be obtained via evaluating them at the boundaries of the subspaces decomposed. So the unmatched fuzzy basis functions can be handled in stability analysis of the resulting closed-loop systems with support of these local representations. Then by employing a matrix decomposition technique which is effective in dealing with linear fractional uncertainties which involve a multidimensional Wiener process, a state feedback controller is developed such that the resulting closed-loop IT2 system is stochastically asymptotically stable. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.
机译:本文涉及具有维纳过程和无匹配前提的区间类型2(IT2)不确定Ito随机模糊系统的状态反馈控制。不确定性具有线性分数形式,不仅出现在隶属函数中,而且还出现在系统的参数矩阵中。要设计的控制器的模糊基础功能与IT2模糊模型的功能不同。由于底层系统涉及随机扰动和不匹配的前提以及参数不确定性,因此与确定性系统相比,稳定问题变得更加复杂和具有挑战性。通过空间分解,可以根据一些局部基函数的凸组合来局部表示上下隶属函数(LUMF),可以通过在分解的子空间的边界处对其求值来获得系数。因此,在支持这些局部表示的情况下,可以在所得闭环系统的稳定性分析中处理无与伦比的模糊基函数。然后,通过采用可有效处理涉及多维维纳过程的线性分数不确定性的矩阵分解技术,开发了一种状态反馈控制器,从而使所得的闭环IT2系统随机渐近稳定。最后,给出了一个仿真实例,说明了该方法的有效性。 (C)2015 Elsevier B.V.保留所有权利。

著录项

  • 来源
    《Neurocomputing》 |2016年第3期|1082-1095|共14页
  • 作者单位

    Hangzhou Dianzi Univ, Sch Automat, Inst Informat & Control, Hangzhou 310018, Zhejiang, Peoples R China|Hangzhou Dianzi Univ, Sch Sci, Hangzhou 310018, Zhejiang, Peoples R China;

    Hangzhou Dianzi Univ, Sch Automat, Inst Informat & Control, Hangzhou 310018, Zhejiang, Peoples R China;

    Hangzhou Dianzi Univ, Sch Automat, Inst Informat & Control, Hangzhou 310018, Zhejiang, Peoples R 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

    Interval type-2 fuzzy system; Stochastic system; Unmatched premises; Parametric uncertainty;

    机译:区间2型模糊系统随机系统前提不匹配参数不确定性;

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