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仿射非线性系统的在线自适应模糊神经网络辨识与控制
引用本文:李晓秀,刘国荣,沈细群. 仿射非线性系统的在线自适应模糊神经网络辨识与控制[J]. 湖南大学学报(自然科学版), 2006, 33(4): 64-67
作者姓名:李晓秀  刘国荣  沈细群
作者单位:1. 湖南工程学院,电气与信息工程系,湖南,湘潭,411101
2. 湖南工程学院,电气与信息工程系,湖南,湘潭,411101;湖南大学,电气与信息工程学院,湖南,长沙,410082
基金项目:湖南省自然科学基金资助项目(01JJY2062)
摘    要:针对单输入单输出非线性系统的自适应控制问题,提出了一种在线自适应模糊神经网络辨识与鲁棒控制的方法.该方法首先利用广义模糊神经网络学习算法,实时建立对象模型未知系统的逆动态模型,实现网络结构和参数的同时在线自适应.考虑到网络建模误差和外部干扰的存在,还设计了基于控制理论的鲁棒补偿器.仿真结果表明,该方法能对模型未知仿射非线性系统实现鲁棒输出跟踪.

关 键 词:模糊神经网络  自适应  鲁棒控制  仿射非线性系统
文章编号:1000-2472(2006)04-0064-04
收稿时间:2006-03-12
修稿时间:2006-03-12

Online Adaptive Fuzzy Neural Network Identification and Control for the Affine Nonlinear Systems
LI Xiao-xiu,LIU Guo-rong,SHEN Xi-qun. Online Adaptive Fuzzy Neural Network Identification and Control for the Affine Nonlinear Systems[J]. Journal of Hunan University(Naturnal Science), 2006, 33(4): 64-67
Authors:LI Xiao-xiu  LIU Guo-rong  SHEN Xi-qun
Affiliation:1.Dept of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan, Hunan 411101 ,China; 2. College of Electrical and Information Engineering, Hunan Univ, Changsha, Hunan 410082, China
Abstract:An online adaptive fuzzy neural network identification and robust control approach were proposed for the adaptive control problem of SISO nonlinear system.First,the generalized fuzzy neural network(G-FNN) learning algorithm was used to model the unknown system inverse dynamics real-time so that the network structure and parameters could be self-adaptive simultaneously.Then,due to the existences of G-FNN modeling error and external disturbance,a robust compensator was designed based on control theory.Simulation results showed that the proposed approach could achieve the robust tracking of the unknown nonlinear system.
Keywords:fuzzy neural network  adaptive  robust control  affine nonlinear systems
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