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

By Abdulkadir Zirek and Bekir Tuna Kayaalp


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

Topics: adaptive, single neuron, slip, learning algorithm, control, adhesion, traction
Publisher: University of Pardubice
Year: 2018
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