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(英文)[J].控制理论与应用,2001,18(3):456~460.[点击复制]
LI Xiang,CHEN Zeng-qiang,YUAN Zhu-zhi.Simple Recurrent Neural Network Control for Non-minimum Phase Nonlinear System[J].Control Theory and Technology,2001,18(3):456~460.[点击复制]
非最小相位非线性系统的简单递归神经网络控制(英文)
Simple Recurrent Neural Network Control for Non-minimum Phase Nonlinear System
摘要点击 1239  全文点击 1249  投稿时间:2000-07-07  修订日期:2001-01-15
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DOI编号  10.7641/j.issn.1000-8152.2001.3.027
  2001,18(3):456-460
中文关键词  简单递归神经网络  非最小相位系统  非线性系统  神经网络控制
英文关键词  simple recurrent neural networks  non minimum phase system  nonlinear system  neural network control
基金项目  
作者单位
李 翔 南开大学 自动化系, 天津 300071 
陈增强 南开大学 自动化系, 天津 300071 
袁著祉 南开大学 自动化系, 天津 300071 
中文摘要
      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器的推广. 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.
英文摘要
      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.