Reliability-based design optimization for flexible mechanism with particle swarm optimization and advanced extremum response surface method

作     者：张春宜 宋鲁凯 费成巍 郝广平 刘令君 ZHANG Chun-yi;SONG Lu-kai;FEI Cheng-wei;HAO Guang-ping;LIU Ling-jun

作者机构：School of Mechanical and Power Engineering Harbin University of Science and Technology School of Computer Science and Engineering Beihang University Department of Mechanical Engineering The Hong Kong Polytechnic University 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2016年第23卷第8期

页      面：2001-2007页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Projects(51275138,51475025)supported by the National Natural Science Foundation of China Project(12531109)supported by the Science Foundation of Heilongjiang Provincial Department of Education,China Projects(XJ2015002,G-YZ90)supported by Hong Kong Scholars Program,China Project(2015M580037)supported by Postdoctoral Science Foundation of China 

主　　题：reliability-based design optimization flexible robot manipulator artificial neural network particle swarm optimization advanced extremum response surface method 

摘      要：To improve the computational efficiency of the reliability-based design optimization(RBDO) of flexible mechanism, particle swarm optimization-advanced extremum response surface method(PSO-AERSM) was proposed by integrating particle swarm optimization(PSO) algorithm and advanced extremum response surface method(AERSM). Firstly, the AERSM was developed and its mathematical model was established based on artificial neural network, and the PSO algorithm was investigated. And then the RBDO model of flexible mechanism was presented based on AERSM and PSO. Finally, regarding cross-sectional area as design variable, the reliability optimization of flexible mechanism was implemented subject to reliability degree and uncertainties based on the proposed approach. The optimization results show that the cross-section sizes obviously reduce by 22.96 mm^2 while keeping reliability degree. Through the comparison of methods, it is demonstrated that the AERSM holds high computational efficiency while keeping computational precision for the RBDO of flexible mechanism, and PSO algorithm minimizes the response of the objective function. The efforts of this work provide a useful sight for the reliability optimization of flexible mechanism, and enrich and develop the reliability theory as well.