traction control

Fuzzy controller, designed by reinforcement learning, for vehicle traction system application

In this article, a fuzzy controller tuned by reinforcement learning is proposed.  The developed algorithm utilizes a fuzzy logic theory and a reinforcement learning for fine-tuning parameters of the membership function for the fuzzy controller.  Apart from the fuzzy controller developed, a fuzzy corrector of reference input (set-point) signal to the controller is applied.  The fuzzy corrector changes the input (reference) signal of the system and takes into account an original reference input and type of external disturbances.