Sliding mode control for urban railway anti-slip system based on optimal slip ratio estimation with forgetting factor recursive least-squares

Abstract

It is a key issue to ensure the safe operation of urban railway vehicle by avoiding the phenomenon of wheel slipping or locking under braking conditions, which can be implemented by looking for and keeping an optimal slip ratio. In this paper, the problem of anti-slip control for urban railway vehicle based on optimal slip ratio is studied. Forgetting factor recursive least-squares (FFRLS) algorithm is proposed to estimate the optimal slip ratio online according to the relationship between adhesion coefficient and slip ratio. By dynamically adjusting the forgetting factor, the optimal slip ratio is estimated in real time when the rail environment changes during vehicle braking process. Meanwhile, the unmeasurable adhesion force is estimated by the disturbance observer with a first-order low-pass filter. Based on the optimal slip ratio, sliding mode control with chattering suppression is adopted to obtain the optimal control input, which can solve the strong external disturbance problem and suppress high frequency chattering of the control input. Simulation results validate the effectiveness of the proposed control strategy.