引用本文:马俊峰,张庆灵.T-S模糊广义系统的逼近性[J].控制理论与应用,2008,25(5):837~844.[点击复制]
MA Jun-feng,ZHANG Qing-ling.Approximation property of T-S fuzzy singular systems[J].Control Theory and Technology,2008,25(5):837~844.[点击复制]
T-S模糊广义系统的逼近性
Approximation property of T-S fuzzy singular systems
摘要点击 1491  全文点击 1282  投稿时间：2006-08-20  修订日期：2007-12-28
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DOI编号  10.7641/j.issn.1000-8152.2008.5.008
  2008,25(5):837-844
中文关键词  T-S模糊广义系统  逼近性  非线性广义系统  神经网络
英文关键词  T-S fuzzy singular systems  approximation property  nonlinear singular systems  neural network
基金项目  国家自然科学基金资助项目(60574011); 东北大学 流程工业综合自动化教育部重点实验室资助项目.
作者单位E-mail
马俊峰 东北大学 系统科学研究所, 辽宁 沈阳 110004 junfeng_ma_china@yahoo.com.cn 
张庆灵 东北大学 系统科学研究所, 辽宁 沈阳 110004 qlzhang@mail.neu.edu.cn 
中文摘要
      本文研究T-S模糊广义系统的逼近性, 给出了T-S模糊广义系统的逼近性定理. 证明其可以以任意的精度逼近一类广泛存在的非线性广义系统. 还将MISO(多输入单输出)情况推广到MIMO(多输入多输出)的情况. 在逼近性定理的基础上, 利用神经网络的方法对非线性广义系统建模, 给出了神经网络的结构及学习算法. 本文共提出了两种神经网路的训练策略, 对各自的优点与不足给出了分析, 最后用数值例子验证了算法的有效性.
英文摘要
      This article focuses on the approximation problem of T-S fuzzy singular systems. An approximation theorem of T-S fuzzy singular systems is proposed. It demonstrates that T-S fuzzy singular systems could approximate to a wide class of nonlinear singular systems with arbitrarily high accuracy. The MISO (multi-input single-output) situation is extended to MIMO (multi-input multi-output) situation. Based on this approximation theorem and using neural network method, the model of T-S fuzzy singular systems can be constructed along with its learning algorithm. Two neural network training strategies are also proposed and their advantages and disadvantages are analyzed respectively. Finally, a numerical example is given to illustrate the validity of the algorithms.