Inertia Parameter Identification of Robot Arm Based on BP Neural Network
The modeling and controlling of robot dynamics are two important fields in the robotics.Modeling is the precondition of controlling.Accurate model parameters obtained can improve the control precision.In the paper,the dynamic model of a robot arm is built with the Newton-Euler method and transformed into linear equations about inertia parameters for identification.By operating the robot arm,the system input and output data can be abstracted and a BP neural network is to create.The 10 inertia parameters of every connecting rod are regarded as the weights of the neural network.The errors of output torques between the original system and the neural network are used to adjust the weights.Finally,the results of inertia parameters identification are obtained.Then take a two degree-of-freedom robot arm as an example.The simulation result verifies the validity of inertia parameter identification based on neural network.
Newton-Euler method Inertia parameters BP neural network Weights
Zhu Qidan Mao Shuang
College of Automation,Harbin Engineering University,Harbin 150001,China
国际会议
The 33th Chinese Control Conference第33届中国控制会议
南京
英文
6605-6609
2014-07-28（万方平台首次上网日期，不代表论文的发表时间）