Robust Learning Control for a Class of Uncertain Linear Motor Systems

Abstract

The tracking problem for a class of linear motor systems with unknown input deadzone is addressed in this paper. Alignment condition is adopted to solve the initial position problem for iterative learning control systems, with the control law and learning laws being developed according to Lyapunov method. Iterative learning control technique and robust control technique are together adopted to compensate uncertainties and disturbances. The position state and velocity state can accurately track the desired trajectories over the whole interval, as the iteration number increases. In the end, a simulation example is presented to demonstrate the effectiveness of the designed control scheme.