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高阶非线性控制系统的适应性仿真研究 被引量:3

Control of High-order Nonlinear Systems and Its Adaptability Simulations
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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。 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.
出处 《系统仿真学报》 EI CAS CSCD 北大核心 2007年第8期1749-1753,共5页 Journal of System Simulation
基金 国家自然科学基金项目(50376029)。
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 high-order nonlinear systems Neural Network Taylor series Monte-Carlo stochastic methods
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参考文献10

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