Design of a Direct Neural Braking System based on Switching Gains Controller


Abstract- In this paper, direct neural controller for braking system is proposed.Learning of the presented controller depends on the training data that comes fromrunning the switching gain controller at different conditions of drive. The training dataconsist of relative velocity error, distance error and braking force. The feed-forwardneural network is used to build direct neural controller with two hidden layers and usingback-propagation training algorithm. The performance of the presented controller isvalidated using nonlinear braking model. Simulation results show the presentedcontroller is able to prevent the collision of vehicles at different driving conditions.Also, the results show superiority of the direct neural controller in comparison with theswitching gain controller at all drive cases that are tested in this work.