Object Property Identification Using Uncertain Robot Manipulator

摘要：

　　This paper presents a learning control algorithm to identify object properties by an uncertain robot manipulator.On one hand,for the robot system with unknown(or immeasurable)parameters,the manipulator dynamics properties are uncertain so we use adaptive parameter learning law to estimate the practically unknown dynamics.On the other hand,a reference model is specified to be followed.In order to identify the geometry and elasticity of the interacting object,the reference point and feedforward force in reference model is adapted in each trial.Because the updating of the reference model utilizes the estimated parameters,the learning law of parameter estimation is thus designed to guarantee the convergence of parameter estimation in finite time(FT).Simulation studies demonstrate the effectiveness of our proposed method.

关键词： Unknown parameter estimation Object property identification Reference model Adaptive control

作者: Kunxia Huang Chenguang Yang Hong Cheng

作者单位: Key Laboratory of Autonomous Systems and Networked Control,College of Automation Science and Enginee Key Laboratory of Autonomous Systems and Networked Control,College of Automation Science and Enginee Center for Robotics,University of Electronic Science and Technology of China,Chengdu 611731,Sichuan,

会议类型: 国际会议

会议名称: 第七届全国模式识别学术会议(The 7th Chinese Conference on Pattern Recognition,CCPR2016)

会议地点: 成都

会议语种:英文

页码: 174-188

在线出版日期: 2016-11-03（万方平台首次上网日期，不代表论文的发表时间）