Optimal operation of high-speed train based on fuzzy model predictive control

Abstract

Focusing on exploring optimal control method of high-speed train, this research explicitly introduces a fuzzy predictive control framework to enhance safety, comfort, and energy-efficiency. The dynamic equation of the high-speed train is modeled as a cascade of cars connected by spring-like couplers and then represented by Takagi-Sugeno fuzzy model. Based on model predictive control approach, an effort is made on the design of fuzzy predictive controller such that each car tracks the target speed, and every coupler is stabilized to the equilibrium state as well as optimizing the performance function value at every time instant with regard to accelerating and braking constraints. Sufficient conditions for the existence of corresponding controller optimization problem are given in a set of linear matrix inequalities. Some simulations are performed to show the effectiveness of the model and the algorithm.