Optimal Operation of High-Speed Trains Using Hybrid Model Predictive Control

Yingze Yang,Rui Zhang,Weirong Liu,Zheng Xu,Zhiwu Huang,Heng Li

doi:10.1155/2018/7308058

Abstract

The high-speed train operation process is highly nonlinear and has multiple constraints and objectives, which lead to a requirement for the automatic train operation (ATO) system. 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 through 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 mixed-integer linear programming (MILP) technique. Simulation results validate the effectiveness of the proposed method.

Highlights

With rapid development of high-speed railway, the operation safety, punctuality, and energy consumption of train have received more and more attentions
The automatic train operation (ATO) system is the essential component that plays a key role in the train operation process [4]
The problem of automatic train control is established as a constrained finite time optimal control problem and further transformed into mixed integer linear programming (MILP) problem by analyzing the operation target and constraints

Summary

Introduction

With rapid development of high-speed railway, the operation safety, punctuality, and energy consumption of train have received more and more attentions. For online operation process of high-speed trains, it raises the nonlinear resistance force which makes many classical control methods based on the linear resistance force model or the single equilibrium point linearizable model difficult to be implemented. The hybrid MPC controller uses the mixed logic dynamical model to predict the future evolution of the system at each time step, and a certain performance index is optimized under operating constraints with respect to a sequence of future input moves. The first of such optimal solution is the control action applied to the plant.

The Model of High-Speed Train

Hybrid MPC Based ATO Design

Controller Design

Performance Evaluation

Conclusion