The slip control of a tram-wheel test stand model with single neuron PID control method

Abstract

In this study, a single neuron PID (proportional, integral, and derivative) control algorithm is proposed for longitudinal slip control of a tram-wheel test stand. Hebb learning algorithm was employed for tuning the control parameters. The main advantages of the proposed algorithm are adaptivity, self-organizing, and self-learning. The performance of the control strategy is simulated using the mathematical model of the tram-wheel test stand that is developed in MATLAB environment. The simulation results show that the proposed algorithm has better closed-loop performance compared to traditional PID control method.