引用本文:张友旺,桂卫华,赵泉明.基于动态递归模糊神经网络的自适应电液位置跟踪系统[J].控制理论与应用,2005,22(4):551~556.[点击复制]
ZHANG You-wang, GUI Wei-hua, ZHAO Quan-ming.Adaptive electro-hydraulic posittion tracking system based on dynamic recurrent fuzzy neural network[J].Control Theory and Technology,2005,22(4):551~556.[点击复制]
基于动态递归模糊神经网络的自适应电液位置跟踪系统
Adaptive electro-hydraulic posittion tracking system based on dynamic recurrent fuzzy neural network
摘要点击 1143  全文点击 707  投稿时间：2004-02-03  修订日期：2004-08-12
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DOI编号  10.7641/j.issn.1000-8152.2005.4.008
  2005,22(4):551-556
中文关键词  动态递归模糊神经网络  电液位置跟踪系统  变结构控制  鲁棒性
英文关键词  dynamic recurrent fuzzy neural netowrk(DRFNN)  electro-hydraulic position tracking system  variable structure control  robustness
基金项目  
作者单位
张友旺,桂卫华,赵泉明 中南大学信息科学与工程学院,湖南长沙410083
中南大学机电工程学院,湖南长沙410083
湖南大学机械与汽车工程学院,湖南长沙410082 
中文摘要
      提出了动态递归模糊神经网络(DRFNN)以在线估计电液位置跟踪系统中包括非线性、参数不确定性、负载干扰等在内的未知动态非线性函数,基于lyapunov稳定性理论推导出DRFNN可调参数和估计误差的界的自适应律,并构造出稳定的自适应控制器.实验结果表明:基于DRFNN的自适应控制器可使电液位置跟踪系统具有较强的鲁棒性和满意的跟踪性能.
英文摘要
      Dynamic recurrent fuzzy neural network(DRFNN) is proposed to evaluate online the unknown dynamic nonlinear functions that include nonlinearity,parameter uncertainty,load disturbance et al.in electro-hydraulic position tracking system,adaptive laws of the adjustable parameters and the evaluation error bounds of DRFNN are formulated based on Lyapunov stability theory,and a stable adaptive controller is synthesized.The experimental results show that the adaptive controller based on DRFNN can make electro-hydraulic position tracking system more robust and obtain satisfactory tracking performance.