A multiple-model adaptive tracking scheme for high-speed train motion control

Abstract

This paper develops a multiple-model adaptive control scheme for high-speed train system models with uncertain parameters. Using a system signal identity, an indirect adaptive control framework is derived based which multiple parameter estimators are designed with different adaptation gains to generate multiple estimates of uncertain system parameters for constructing multiple adaptive control signals. A control switching mechanism is employed to select the most preferred control signal based on the minimal estimation error. Such a multiple-model adaptive control scheme is more effective in handling parameter uncertainties and tracking a desired velocity trajectories with a better adaptation gain than a singlemodel adaptive controller, leading to improved system transient performance. Simulation results on a high-speed train model verify the desired system stability and tracking properties of the developed multiple-model adaptive control scheme.