| 一类非线性系统基于Backstepping的自适应鲁棒神经网络控制 |
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| 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. |
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| 作者姓名： | 杨小军 李俊民 |
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| 作者单位： | 1. 西北工业大学,自动控制系,应用数学系,陕西,西安,710072
2. 西安电子科技大学,应用数学系,陕西,西安,710071 |
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| 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.
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| 关 键 词： | 非线性自适应控制 backstepping 神经网络 自适应界化 |
| 文章编号： | 1000-8152(2003)04-0589-04 |
| 收稿时间： | 2001/2/26 0:00:00 |
| 修稿时间： | 2001年2月26日 |
Adaptive robust neural network control for a class of nonlinear systems using backstepping |
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| YANG Xiao-jun and LI Jun-min.Adaptive robust neural network control for a class of nonlinear systems using backstepping[J].Control Theory & Applications,2003,20(4):589-592. |
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| Authors: | YANG Xiao-jun and LI Jun-min |
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| Affiliation: | Department of Automatic Control, Applied Mathematics, Northwest Polytechnic University, Shanxi Xi' an 710072, China;Department of Applied Mathematics, Xi Dian University, Shanxi Xi' an 710071, China |
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| Abstract: | 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. |
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| Keywords: | nonlinear adaptive control backstepping neural network adaptive bounding |
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