Fast Iterative Learning Angle Synchronization Control For Hybrid Manipulator System

With the development of industrial automation,manipulators had widely used in automotive,aerospace,and semiconductor industries,and their operational tasks have become more complicated and diversified,they have not limited them to repetitive pipeline tasks and require high-precision trajectory tracking.The hybrid manipulator system composed of multiple serial manipulators in parallel can complete complex tasks.The hybrid manipulator system has the characteristics of high nonlinearity,strong coupling,and difficulty accurately identify parameters,and it is difficult to guarantee the accuracy of collaborative work.The synchronized movement of the research system can lay the foundation for collaborative work.In this paper,a new fast iterative learning angle synchronization control law had designed for a hybrid manipulator system with joint friction,and we analyze its control performance.The specific work is as follows.(1)For a four-degree-of-freedom hybrid manipulator,the nonlinear Lu Gre friction model of the joint had considered,and we established the dynamic model of the system through the Lagrangian equation.(2)Given the high nonlinearity and task repeatability of the hybrid manipulator system,an iterative learning controller had selected.This paper analyzes the geometric relationship of vectors,constructs a new fast iterative learning control law(FILSC)based on P-type iterative learning control(PILC),and proves its convergence through compressed mapping and fixed point principle.The angle synchronization control of the hybrid manipulator system had simulated in Matlab/Simulink,and the influence of parameters such as the number of iterations,expansion factor and initial state in FILSC on the control effect had analyzed.The simulation results show that FILSC has a better control effect than PILC.Simultaneously,the PID-type iterative learning control law had constructed according to the FILSC construction method,and we analyze the portability of the construction method.The simulation shows that it has good portability.(3)In view of the degradation of the angle synchronization control performance after the disturbance,a robust term had added to FILSC and a gain switching function had introduced to design a robust fast iterative learning control to improve the system's anti-interference ability and angle synchronization control performance.Aiming at the influence of the initial value error on the time to enter the steady state,the initial state learning law had introduced,and the fast iterative learning control of initial value learning had designed to weaken the influence of the initial error on the control effect.We proved the two improved FILSCs converge,and the simulation shows that the control effect had effectively improved.