Abstract
Vehicle traction control systems draw much more
attention than ever before while increasing number of projects are conducted on intelligent transportation systems, especially on automated highway systems. There are many efforts to get better systems robust to vehicle uncertainties, noise and changes in the parameters. Neuro-adaptive PID control is a newly proposed control algorithm that takes benefit of the theory of neural networks.
In this study, a neural network trained on-line by sliding mode backpropagation algorithm, which is also newly proposed type of learning, is used in the control structure of the Antilock Braking System. Many simulations on the control system built are carried out to analyze different aspects of it and results are discussed
following them.
