Identification and Control of Flexible Joint Robot Using Multi-Time-Scale Neural Network
用 Multi-Time-Scale 神经网络的灵活联合机器人的鉴定和控制作者机构：Department of MechanicalIndustrial&Aerospace EngineeringConcordia UniversityMontreal H3G 1M8Canada College of Mechanical Sz Electrical EngineeringNanjing University of Aeronautics and AstronauticsNanjing 210016China Department of Electrical and Computer EngineeringConcordia UniversityMontreal H3G 1M8Canada
出 版 物：《Journal of Shanghai Jiaotong university(Science)》 (上海交通大学学报（英文版）)
年 卷 期：2020年第25卷第5期
页 面：553-560页
核心收录：
学科分类：080202[工学-机械电子工程] 08[工学] 0804[工学-仪器科学与技术] 0802[工学-机械工程]
基 金：the Natural Sciences and Engineering Research Council of Canada(No.N00892)
主 题：flexible joint robotic manipulator multi-time-scale neural network singular perturbation adaptive controller
摘 要：In this paper,a new identification and control scheme for the flexible joint robotic manipulator is ***,by defining some new state variables,the commonly used dynamic equations of the flexible joint robotic manipulators are transformed into the standard form of a singularly perturbed ***,an optimal bounded ellipsoid algorithm based identification scheme using multi-time-scale neural network is proposed to identify the unknown system dynamic ***,by using the singular perturbation theory,an indirect adaptive controller based on the identified model is proposed to control the system such that the joint angles can track the given reference *** closed-loop stability of the whole system is proved,and the effectiveness of the proposed schemes is verified by simulations.
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