Abstract
The train operation process is highly nonlinear and has multiple constraints and objectives, which lead to higher requirements for the automatic train operation (ATO) system of high-speed train. In this paper, a hybrid Model Predictive Control (MPC) framework is proposed for the controller design of the ATO system. Firstly, a piecewise linear system with state and input constraints is constructed though piecewise linearization of the high-speed train's nonlinear dynamics. Secondly, the piecewise linear system is transformed into a mixed logical dynamical (MLD) system by introducing the auxiliary binary variables. For the transformed MLD system, a hybrid MPC controller is designed to realize the precise control under hard constraints. To reduce the online computation complexity, the explicit control law is computed offline by employing the multi-parametric mixed-integer linear programming (mp-MILP) techniques. Simulations results validate the effectiveness of the proposed method.
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