| 引用本文: | 杨小军,李俊民.一类非线性系统基于Backstepping的自适应鲁棒神经网络控制[J].控制理论与应用,2003,20(4):589~592.[点击复制] |
| YANG Xiao-jun,LI Jun-min.Adaptive robust neural network control for a class of nonlinear systems using backstepping[J].Control Theory and Technology,2003,20(4):589~592.[点击复制] |
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| 一类非线性系统基于Backstepping的自适应鲁棒神经网络控制 |
| Adaptive robust neural network control for a class of nonlinear systems using backstepping |
| 摘要点击 1447 全文点击 1125 投稿时间：2001-02-26 修订日期：2002-07-12 |
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| DOI编号 10.7641/j.issn.1000-8152.2003.4.023 |
| 2003,20(4):589-592 |
| 中文关键词 非线性自适应控制 backstepping 神经网络 自适应界化 |
| 英文关键词 nonlinear adaptive control backstepping neural network adaptive bounding |
| 基金项目 |
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| 中文摘要 |
| 针对一类未知非线性系统提出了一种基于Backstepping的自适应神经网络控制方法, 放松了满足匹配条件, 要求神经网络逼近误差的边界已知等一些限制性的假设. 扩展了自适应backstepping和自适应神经控制的适用范围, 整个闭环系统表明是最终一致有界的, 跟踪误差收敛于原点的一个大小可调的邻域. |
| 英文摘要 |
| The adaptive neural control scheme was formulated for a class of unknown nonlinear systems based on backstep-ping technique. The proposed scheme relaxed the requirements of matching condition and of a known bound on the network reconstruction. The method expands the applicable scope of the class of nonlinear systems, which can successfully utilize the backestepping algorithm and adaptive NN control .The resulting closed-loop system is proven to be ultimately uniform bounded, and the output tracking error converges to an adjustable neighborhood of zero. |