Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2017, Vol. 40 ›› Issue (4): 35-40.doi: 10.13190/j.jbupt.2017.04.006

• Papers • Previous Articles     Next Articles

Automatic Updating Response Surface Method for Motion Trajectory Reliability Analysis of Manipulator

FENG Jia-zhen1,2, ZHANG Jian-guo1,2, JIA Qing-xuan3, CHEN Gang3, SUN Jing-yi1,2   

  1. 1. School of Reliability and Systems Engineering, Beihang University, Beijing 100191, China;
    2. Science and Technology on Reliability and Environmental Engineering Laboratory, Beihang University, Beijing 100191, China;
    3. School of Automation, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2017-03-22 Online:2017-08-28 Published:2017-07-10

Abstract: In order to solve the efficiency and accuracy problem appeared in motion trajectory reliability analysis of the manipulator, a new automatic updating response surface method is presented. Firstly, based on the equivalent extreme value approach, the motion trajectory reliability analysis is converted into the reliability analysis about the trajectory point in which the motion error reaches its maximum. Secondly, for different random sample inputs, the particle swarm optimization algorithm is employed to get the time responses corresponding to the maximum values of the motion errors. These inputs and time responses are used to construct a Kriging response surface of time, which is used to get the estimated value of the time response rapidly and improve the efficiency of the reliability analysis. Thirdly, based on the mean square predicted error, an automatic updating mechanism is constructed. Through adding new sample points, the approximate quality of the Kriging response surface is improved, and the accuracy of the reliability analysis results is assured. A case analysis is used to demonstrate the validity of the proposed method.

Key words: manipulator, motion trajectory reliability, automatic updating response surface method, Kriging, particle swarm optimization algorithm, relative mean square predicted error

CLC Number: