Supervisory Control of Chaotic Systems Using Online GA Tuning Neural Networks
会议名称：《第二十六届中国控制会议》
会议日期：2007年
学科分类：12[管理学] 07[理学] 08[工学] 071101[理学-系统理论] 071102[理学-系统分析与集成] 0711[理学-系统科学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 0835[工学-软件工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 081103[工学-系统工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：supported by National Nature Science Foundation under Grant 50537030
关 键 词：Neural Networks Genetic Algorithms Supervisory Control Chaos
摘 要：In this paper,we present a controller for the supervisory backstepping control of a class of general nonlinear sys- tems using online GA tuning neural networks （GNSB controller）.The weights of the neural networks （NNs） approximator employed in the backstepping controller can successfully be turned via an online genetic algorithms （GAs） *** ge- netic algorithm has the capability of directed random search for global optimization.A simplified form of GA （SGA） ap- proach is proposed to accelerate the search speed,and a new fitness function is established by the Lyapunov design method for the requirement of tuning the weights of the NNs online.A supervisory controller is used to guarantee the stability of the close-loop nonlinear *** of Duffing chaotic system controlled by the presented controller are shown to illustrate the effectiveness of the proposed controller.