Research On Passivity Robust Control For SNR6 Industrial Robot Based On Parameter Identification

As an advanced processing and manufacturing equipment system with multiple inputs,multiple outputs,and intelligence,industrial robots are widely used in fields such as automobiles,aviation,and aerospace due to their strong applicability,high efficiency,and good economy.The products in the aforementioned fields have the characteristics of large size,complex structure,and heavy load during processing and manufacturing.Industrial robots often need to work under high-speed and heavy-load conditions,and their dynamic characteristics have a significant impact on the control accuracy of the system.Therefore,it is necessary to consider the dynamic characteristics of the robot in the control system,that is,to control the robot based on its dynamic model.However,the dynamic model of industrial robots has the characteristics of high nonlinearity and strong coupling,and the parameter decoupling and identification are difficult.The uncertainty of parameter identification errors and load interference has a significant impact on the accuracy of dynamic control.In view of this,this paper studies the parameter identification and dynamic robust control methods of industrial robot.Firstly,taking the SNR6 industrial robot as the research object,its forward and inverse kinematic models are analyzed and calculated,and the SNR6 industrial robot dynamic model with friction term is established using the Euler-Lagrange method.Secondly,the minimum parameter set of the robot dynamic model is identified using the least squares method,and the robot dynamic full parameter model is solved by analyzing the robot dynamic model before and after parameter linearization.Thirdly,the parameter identification error and load interference of the robot model are analyzed,and an uncertain SNR6 industrial robot dynamic model is established.A passive robust controller for the SNR6 industrial robot is designed based on the passive control theory,which includes a passive control part based on the robot dynamic identification model and an adaptive robust control part based on online identification of uncertainty boundary information.The stability of the proposed controller is proved by using the boundedness theory.Then,with the help of the joint simulation of Solidworks and Simulink,different working conditions are simulated,and the proposed control method is numerically simulated to preliminarily verify its effectiveness.Finally,based on Twin CAT3,the experimental platform of the SNR6 industrial robot control system is built,the development of the main functional modules of the control system is completed,and the experimental verification scheme of different working conditions is designed.The feasibility and advancedness of the proposed control method are further verified by comparing with the PID control method based on inverse dynamics.