Adaptive Iterative Learning Control of Robotic Manipulator with Second-Order Terminal Sliding Mode Method

Abstract

To solve the trajectory tracking problem of robotic manipulators with uncertain model information and unknown external disturbances, an adaptive iterative learning control method with second-order terminal sliding mode method is proposed in this paper. This method adopts nonsingular fast terminal sliding mode surface and second-order sliding mode control to improve the convergence speed of system states and robustness. Adaptive iterative learning control is used to approximate system model and bounded external disturbance for getting rid of the dependence on specific mathematical model and improving control precision. The convergence of this controller along iterative times is proved by composite energy function. With Denso VP6242G manipulator as the controlled object, this proposed controller has better performance comparing to traditional iterative learning controller designs.