工程科学学报2017，Vol.39Issue(4)：611-618,8.DOI:10.13374/j.issn2095-9389.2017.04.017
函数型数据分析与优化极限学习机结合的弹药传输机械臂参数辨识
Parameter identification of a shell transfer arm using FDA and optimized ELM
摘要
Abstract
To identify the unmeasurable parameters of a shell transfer arm,a virtual prototype of the shell transfer arm was built,and the built virtual prototype is regard as the source of the sample data.Considering the continuity and smoothness properties of the sample data,features of the curves were extracted by functional data analysis and functional principal component analysis,and the features and unknown parameters were used to train the extreme learning machine(ELM).At the meantime,the weight connecting the input layer and hidden layer and the threshold of the hidden nodes were optimized by particle swarm optimization(PSO)to improve the identification accuracy and generalization performance of ELM.At last,the presented method was verified by simulation data and test data.The identification results of the simulation data show that the optimized ELM has higher identification accuracy and better generalization performance.Also,the presented method is proved to be feasible and effective by comparing the real angular velocity and the angular velocity from the virtual prototype with respect to the test data identification results.关键词
参数辨识/函数型数据分析/极限学习机/粒子群优化/弹药传输机械臂Key words
parameter identification/functional data analysis/extreme learning machine/particle swarm optimization/shell transfer arm分类
信息技术与安全科学引用本文复制引用
赵抢抢,侯保林..函数型数据分析与优化极限学习机结合的弹药传输机械臂参数辨识[J].工程科学学报,2017,39(4):611-618,8.基金项目
国家自然科学基金资助项目(51175266) （51175266）
国家高技术研究发展计划资助项目(6132490102) （6132490102）
