引用本文:王 源, 胡寿松, 吴庆宪.一类非线性系统的自组织模糊CMAC神经网络自适应重构跟踪控制[J].控制理论与应用,2003,20(1):70~72.[点击复制]
WANG Yuan, HU Shou-song, WU Qing-xian.Adaptive reconfigurable tracking control of a class of nonlinear systems based on self-organizing fuzzy CMAC neural networks[J].Control Theory and Technology,2003,20(1):70~72.[点击复制]
一类非线性系统的自组织模糊CMAC神经网络自适应重构跟踪控制
Adaptive reconfigurable tracking control of a class of nonlinear systems based on self-organizing fuzzy CMAC neural networks
摘要点击 1304  全文点击 1661  投稿时间:2001-05-15  修订日期:2002-02-28
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DOI编号  10.7641/j.issn.1000-8152.2003.1.015
  2003,20(1):70-72
中文关键词  重构控制  小脑模型关联控制器  非线性系统  自适应
英文关键词  reconfigurable control  CMAC  nonlinear systems  adaptation
基金项目  国家自然科学重点基金(60234010); 航空科学重点基金(98Z51002); 博士点基金(2000028704)资助项目
作者单位E-mail
王 源, 胡寿松, 吴庆宪 南京航空航天大学 自动化学院,江苏南京 210016 liuyaly@263.net 
中文摘要
      提出了一种非线性系统的自组织模糊CMAC(SOFCMAC)神经网络自适应重构跟踪控制方法,首先通过构造增广系统,设计出线性渐近跟踪控制器,然后采用SOFCMAC神经网络在线重构系统的非线性特性,以消除非线性特性引起的系统误差,可保证非线性系统闭环稳定并使系统输出跟踪期望输出.仿真算例证明了SOFCMAC神经网络自适应重构跟踪控制系统的稳定性.
英文摘要
      This paper presents a method of adaptive reconfigurable tracking control of a class of nonlinear systems based on self-organizing fuzzy CMAC neural networks. First a linear asymptotic tracking controller is designed by constructing an augmented system. Then the on-line learning-while controlling neural network SOFCMAC is used to eliminate the error caused by the system nonlinearities, which will guarantee the system stability and tracking of system output to desired output. The stability of the system is proved.