PDF control of robotic systems with non-Gaussian disturbances

被引：0
作者：
Chen, Haiyong [1 ]
Wang, Hong [2 ]
Xu, De [1 ]
机构：
[1] Chinese Acad Sci, Inst Automat, Beijing 100080, Peoples R China
[2] Univ Manchester, Control Syst Ctr, Sch Elect & Elect Engn, Manchester M60 1QD, Lancs, England
来源：
SEVENTH INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION AND CONTROL TECHNOLOGY: OPTOELECTRONIC TECHNOLOGY AND INSTUMENTS, CONTROL THEORY AND AUTOMATION, AND SPACE EXPLORATION | 2008年 / 7129卷
关键词：
probability density function control; manipulator control; non-Gaussian noises; iterative learning control;
D O I：
10.1117/12.807450
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 study, the probability density function (PDF) control method has been developed to deal with the random tracking error for a class of robotic manipulator that are subjected to non-Gaussian noises. The control aim is that the shape of the PDF of the tracking error is made as close as possible to the desired PDF. The ILC frame about PDF control approach of manipulators system with non-Gaussian noises has been proposed and a recursive optimization solution batch-by-batch has been developed. In each batch, nonlinear closed-loop error dynamics is considered. In addition, the convergence condition of the tracking control algorithm has been analyzed. Finally, a simulation is given to illustrate the efficiency of the proposed approach.
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页数：7
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