| 基于多层神经网络的饱和非线性输入自适应控制 |
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| 引用本文： | 李红春,梅建东,任云晖.基于多层神经网络的饱和非线性输入自适应控制[J].扬州职业大学学报,2011,15(1):33-36,39. |
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| 作者姓名： | 李红春 梅建东 任云晖 |
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| 作者单位： | 1. 江海职业技术学院,扬州,225101
2. 扬州职业大学,扬州,225009 |
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| 摘 要： | 针对一类具有未知饱和模型的单输入单输出非线性系统的控制问题,根据滑模控制原理和多层神经网络的逼近能力,提出了一种直接自适应神经网络控制器的设计新方案。该方法将控制增益推广到未知函数,通过补偿饱和模型方法取消了饱和模型各参数已知的条件。鲁棒项的引入消除了建模误差和参数估计误差的影响。理论分析证明了闭环系统是半全局一致终结有界,跟踪误差收敛到零的邻域内。仿真结果进一步表明所提控制方法的有效性。
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| 关 键 词： | 自适应控制 神经网络 饱和 非线性控制 |
Adaptive Control with Saturation Nonlinear Input Based on Multi-Neural Networks |
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| LI Hong-chun,MEI Jian-dong,REN Yun-hui.Adaptive Control with Saturation Nonlinear Input Based on Multi-Neural Networks[J].Journal of Yangzhou Polytechnic College,2011,15(1):33-36,39. |
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| Authors: | LI Hong-chun MEI Jian-dong REN Yun-hui |
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| Institution: | LI Hong-chun1,MEI Jian-dong2,REN Yun-hui1(1.Jianghai Vocational Institute of Technology,Yangzhou 225101,China,2.Yangzhou Polytechnic College,Yangzhou 225009,China) |
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| Abstract: | The nonlinear system with saturation input is discussed in this paper.Based on the principle of sliding mode control and the approximation capability of multi-neural networks,a new design scheme of adaptive neural network controller is proposed.The control gain is extended to unknown function and the condition of known parameters is canceled by compensating saturation.Robust term is used to eliminate the approximating error and disturbance.By Lyapunov function,the closed-loop system is shown to be uniformly... |
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| Keywords: | adaptive control neural networks saturation nonlinear control |
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