B-spline Decomposition based Iterative Learning Control and its Application in Load Simulator

Load simulator is a kind of hardware in the loop (HIL) simulation equipment, which is used to simulate the real load of the actuator in the laboratory environment. The main goal of the load simulator is to eliminate the surplus torque caused by the movement of the tested actuator and track the load spectrum accurately. When the load simulator tracks the high-frequency load signal, the feedback based control method has a serious lag, which can be avoided by using iterative learning control. However, iterative learning control is suitable for the case of constant reference trajectory and cannot deal with non-repetitive reference trajectory. B-spline decomposition based iterative learning control method is proposed. The reference load spectrum signal is decomposed into the basic spline signal, and the corresponding basic input is obtained by iterative learning control, the final control input is synthesized for tracking reference load spectrum. The simulation and experimental results show that compared with the traditional control method, this method can effectively improve the loading accuracy. The main contribution of this paper is to apply iterative learning control to non repetitive trajectory tracking.