| 非最小相位非线性系统的简单递归神经网络控制 |
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| 引用本文： | 李 翔,陈增强,袁著祉. 非最小相位非线性系统的简单递归神经网络控制[J]. 控制理论与应用, 2001, 18(3): 456-460 |
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| 作者姓名： | 李 翔 陈增强 袁著祉 |
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| 作者单位： | 南开大学自动化系 |
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| 基金项目： | Foundation item:supported by National 863 CIMS Project Foundation (863-511-945-010), Natural Science Foundation of Tianjin (983602011) and University Key Teacher Foundation of Ministry of Education (0065). |
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| 摘 要： | 从简单递归神经网络的统一结构出发设计了简单递归神经网络控制器，在引入了控制加权的目标函数下优化神经网络权值学习，因此是通常意义的神经网络控制的推广。证明了整个系统的稳定性，并通过仿真验证了控制器的有效性。
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| 关 键 词： | 简单递归神经网络 非最小相位系统 非线性系统 控制器 |
| 文章编号： | 1000-8152(2001)03-0456-05 |
| 收稿时间： | 2000-07-07 |
| 修稿时间： | 2000-07-07 |
Simple Recurrent Neural Network Control for Non-minimum Phase Nonlinear System |
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| LI Xiang,CHEN Zeng-qiang and YUAN Zhu-zhi. Simple Recurrent Neural Network Control for Non-minimum Phase Nonlinear System[J]. Control Theory & Applications, 2001, 18(3): 456-460 |
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| Authors: | LI Xiang CHEN Zeng-qiang YUAN Zhu-zhi |
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| Affiliation: | Department of Automation, Nankai University, Tianjin, 300071,P.R.China;Department of Automation, Nankai University, Tianjin, 300071,P.R.China;Department of Automation, Nankai University, Tianjin, 300071,P.R.China |
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| Abstract: | We discuss a uniform structure of simple recurrent neural networks, based on which a novel neural control system is developed. With the introduction of the weighted control information into the neural controller's cost function, the method is an extension of the common neural networks controller proposed before. The stability of the whole neural control system is demonstrated and its effectiveness is verified via simulation. |
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| Keywords: | simple recurrent neural networks non minimum phase system nonlinear system neural network control |
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