非线性时变系统特征建模与自适应迭代学习控制  

CHARACTERISTIC MODELING AND ADAPTIVE ITERATIVE LEARNING CONTROL FOR NONLINEAR TIME-VARYING SYSTEMS

作　　者：孙明轩[1] 毕宏博[1] 张杰[1] 

机构地区：[1]浙江工业大学信息工程学院,杭州310023

出　　处：《系统科学与数学》2016年第4期461-475,共15页Journal of Systems Science and Mathematical Sciences

基　　金：国家自然科学基金(61174034;61573320)资助课题

摘　　要：讨论连续/离散非线性时变系统的特征建模,统一采用一阶时变差分方程作为特征模型.对于建模中可能产生的快变亦或突变的模型参数,以学习辨识方法进行估计;利用参数估值设计自适应迭代学习控制器,实现轨迹跟踪任务.参数估计学习算法包括带有遗忘因子的最小二乘学习算法和梯度学习算法.数值算例和电机位置跟踪实验结果表明所提出特征建模方法和学习控制方案的有效性.This paper presents a characteristic modeling method for continuous-time and discrete-time nonlinear time-varying systems, with a unified model described by a first-order time-varying difference equation. Learning identification algorithms, the least squares/gradient learning algorithms with a forgetting factor, are suggested for the purpose of parameter estimation. On the basis of the parameter estimation, an adaptive iterative learning control strategy is proposed to achieve perfect tracking over a pre-specified finite-time interval. Numerical simulation and experiment on a permanent-magnet synchronous motor are carried out to demonstrate the effectiveness of the modeling and control method.

关 键 词：非线性时变系统 特征模型 学习辨识 自适应迭代学习控制. 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程]