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高阶非线性控制系统的适应性仿真研究
引用本文:王军,李东海,宋跃进. 高阶非线性控制系统的适应性仿真研究[J]. 系统仿真学报, 2007, 19(8): 1749-1753
作者姓名:王军  李东海  宋跃进
作者单位:1. 清华大学热力系统仿真与控制研究所,热科学与动力工程教育部重点实验室,北京,100084
2. 中国兵器工业集团二○七研究所,太原,030006
摘    要:针对带有外部扰动和参数摄动的不确定高阶非线性系统,利用积分行为补偿系统的各种未知因素,设计适应性非线性控制器(ANLC),并提出了全面的控制器适应性评价方法。首先结合典型信号扰动试验和模型参数摄动试验,检验系统的抗扰性和鲁棒稳定性;然后引入神经网络和Taylor级数展开理论构造非线性函数,改变高阶非线性系统的模型结构,利用Monte-Carlo随机试验方法,进行模型摄动的性能鲁棒性分析;并与精确反馈线性化(EFL)方法进行了定量比较。结果表明,适应性非线性控制器(ANLC)具有很强的适应性能,是解决不确定高阶非线性系统控制的有效途径。

关 键 词:高阶非线性系统  神经网络  Taylor级数  Monte-Carlo随机试验方法
文章编号:1004-731X(2007)08-1749-05
收稿时间:2006-03-20
修稿时间:2006-09-05

Control of High-order Nonlinear Systems and Its Adaptability Simulations
WANG Jun,LI Dong-hai,SONG Yue-jin. Control of High-order Nonlinear Systems and Its Adaptability Simulations[J]. Journal of System Simulation, 2007, 19(8): 1749-1753
Authors:WANG Jun  LI Dong-hai  SONG Yue-jin
Affiliation:1 .Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Institute of Simulation and Control for Thermal Power Engineering, Tsinghua Univ., Beijing 100084, China; 2.North Industries Group 207 Research Institute, Taiyuan 030006, China
Abstract:A nonlinear controller(ANLC) for uncertain high-order nonlinear plant with perturbation and disturbance was designed. A method for comprehensive adaptability evaluation was also presented. The controller includes integral actions for compensation of the entire dynamics of system. System disturbances and model parameter uncertainty tests were carried to validate auto-disturbance ability and robustness. In order to verify the performances robustness and adaptability of controller, the Neural Network and the Taylor series were applied to construct nonlinear function, change the weights and biases of the network or the coefficients of Taylor series to remodel the plant. Monte-Carlo stochastic methods were also used to analyze the characteristics of controller. Simulation results compared with exact feedback linearization show that ANLC has good adaptability and it is an effective approach for uncertain high-order nonlinear systems.
Keywords:high-order nonlinear systems  Neural Network  Taylor series  Monte-Carlo stochastic methods
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