Research On Intelligent Sliding Mode Control Of Dual Arm Robot

With the rapid development of science and technology,robots occupy an increasingly important position in the field of industrial automation.Unlike CNC machine tools and other equipment,industrial robots have a strong interaction with the surrounding environment,and the traditional labor force of workers slowly began to be replaced by dual arm robots.Dual arm robot(DAR)with its high coordination,robustness,flexibility,etc.,are widely used in modern manufacturing.The DAR system studied in this paper is mainly used in industrial handling operations.It has high requirements for the position of the end trajectory manipulator of the robot arm.In order to reduce the system tracking error of the DAR end manipulator,in response to its inaccuracy caused by sudden changes in load quality,viscosity and static friction coefficients,and external interference,the backstepping sliding mode control(BSSMC)and intelligent control are designed.And in order to solve the problem of "differential explosion" in backstepping control,dynamic surface control(DSC)is proposed on the basis of BSSMC.Firstly,the research status of the DAR system and its trajectory tracking control method is reviewed,and the kinematics analysis of the DAR itself is carried out.Considering the change of load mass,the uncertain factors and the influence on the tracking performance of the system,the establishment contains the uncertainty DAR dynamics model.In addition,in view of the problem of trajectory tracking at the end of the DAR system,the BSSMC scheme was designed by combining backstepping control and sliding mode control.By using the idea of static compensation,a complete control law was gradually recursively designed,which has high applicability to nonlinear systems.The simulation shows the effectiveness of the BSSMC method,which effectively adjusts and controls the transient uncertainty and disturbances of the DAR nonlinear system and improves the tracking performance.Finally,in order to further improve the tracking performance of the DAR system,radial basis function neural network(RBFNN)and BSSMC are combined to design a backstepping sliding mode controller based on RBFNN.It not only has a good control effect on the existing transient disturbances in the DAR system,but also accurately estimates the existing unknown disturbances and uncertainties,so that the arm end manipulator can accurately track the position,overcome the impact of uncertainty and improve the robust performance of the system.In order to solve the "differential explosion" problem in backstepping control,DSC is proposed,which combines DSC with intelligent control to further improve the control tracking performance.The simulation shows that BSSMC combined with RBFNN can effectively estimate system dynamic disturbances and improve the tracking performance of the system.The DSC method not only ensures tracking accuracy,but also improves the response speed of the system.