Modeling and robust adaptive iterative learning control of a vehicle-based flexible manipulator with uncertainties

被引：33

作者：

Xing, Xueyan ^{[1
]}

Liu, Jinkun ^{[1
]}

机构：

[1] Beijing Univ Aeronaut & Astronaut, Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | 2019年 / 29卷 / 08期

基金：

中国国家自然科学基金;

关键词：

flexible vehicle-mounted manipulator; ODE-PDE model; position regulation; robust adaptive iterative learning control; uncertainties; vibration control; ROBOT MANIPULATOR; SYSTEMS;

D O I：

10.1002/rnc.4500

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this brief, this paper deals with a robust adaptive iterative learning control (ILC) problem for a flexible manipulator attached to a moving vehicle with uncertainties. To begin with, considering the infinite dimensionality of the flexible distributed parameter system, a coupled ordinary differential equation and partial differential equation model is established without any discretization. Then, it is followed by a presentation of an adaptive ILC strategy, which can drive the vehicle and joint to the desired positions based on a proportional-derivative feedback structure with unmodeled dynamics and external disturbances. The deformation of the flexible manipulator can also be suppressed simultaneously under the proposed control laws. By using Lyapunov's direct method, the stability of the closed-loop system is demonstrated. The simulation results are provided to illustrate the effectiveness of the proposed control laws.

引用

页码：2385 / 2405

页数：21

共 35 条

[31] Optimality and flexibility in Iterative Learning Control for varying tasks [J].