An Iterative Predictive Learning Control Approach With Application to Energy Efficient Train Trajectory Tracking

Abstract

An approach of iterative predictive learning control (IPLC) is studied with consideration to both precise train trajectory tracking and energy efficient operation. Through designing the predictive cost function, the IPLC approach for input-affine nonlinear systems is formulated and solved in this paper. Its application to train operation is detailed to compromise between punctuality and energy consumption. Rigorous theoretical analysis confirms that the proposed approach can guarantee the asymptotic convergence of train speed and position to desired profiles along iteration axis. Simulation result shows its effectiveness and enegry efficiency.