| 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] |
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| T-S模糊广义系统的逼近性 |
| Approximation property of T-S fuzzy singular systems |
| 摘要点击 1757 全文点击 1404 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. |
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| 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. |