基于高阶内模的非线性离散系统迭代学习控制  

High-order internal model based iterative learning control scheme for discrete-time nonlinear system

作　　者：周伟[1] 于淼[1] 

机构地区：[1]浙江大学电气工程学院,浙江杭州310027

出　　处：《浙江大学学报（工学版）》2015年第4期754-762,共9页Journal of Zhejiang University：Engineering Science

基　　金：国家自然科学基金资助项目(60974135;61171034);国家"973"重点基础研究发展规划资助项目(2012CB316400)

摘　　要：针对一类工作于重复条件下的一阶非正则离散时间非线性系统追踪迭代域非严格重复的参考轨迹问题,提出基于高阶内模(HOIM)的迭代学习控制方法.利用高阶内模,描述系统输出追踪参考轨迹的迭代域变化规律问题.在针对非线性系统的迭代学习控制律设计过程中,根据内模原理,将高阶内模与D型迭代学习控制律相结合,设计合适的学习增益.从理论上严格证明,在所提出的基于高阶内模的迭代学习控制律的作用下,系统跟踪误差的迭代域收敛性.对机械手离散时间模型的仿真结果表明了该迭代学习控制方法的有效性.A high‐order internal model （HOIM ） based iterative learning control （ILC ） scheme was proposed to tackle the tracking problem under iteration‐varying desired trajectories for discrete‐time nonlinear system with the relative degree of 1 under the repeatable environment .The HOIM was utilized to describe the variation of desired trajectories in the iteration domain .The convergence of tracking error can be guaranteed in the ILC design for the nonlinear systems by incorporating the HOIM into D‐type ILC and appropriately tuning learning control gains according to Internal Model Principle .The rigorous proof was presented to show that the system output could converge to the desired trajectory along the iteration axis under the proposed ILC method . A numerical simulation with discrete‐time robot manipulators demonstrated the effectiveness of the proposed control method .

关 键 词：高阶内模(HOIM) 迭代学习控制(ILC) 迭代变化 离散系统 

分 类 号：TP271[自动化与计算机技术—检测技术与自动化装置]