Tilt control design for high-speed trains: a study on multi-objective tuning approaches

This paper presents work on a hybrid fuzzy control scheme for improving the performance of tilting trains using a nulling-based tilt strategy. Two multi-objective Genetic Algorithm tuning methods (MOGA and NSGAII) were employed to optimise both the fuzzy output membership functions and the controller parameters. The objective functions incorporated the tilt response and roll gyroscope signals for the deterministic (curved track) profile, and lateral acceleration for the stochastic (straight track) profile. Simulation results discuss the effectiveness of using the presented techniques for tuning the fuzzy control scheme via multiple objectives. The proposed scheme is compared with the conventional nulling-tilt approach and a manually-tuned fuzzy controller.