Design of a neuro-controller for vehicle lateral velocity and yaw rate based genetic algorithm with model reference guided

Abstract EN

n this paper, the aim of control problem is to achieve required yaw rate and rom sliding out the Cateral velocity in a short period of time to prevent vehicle؛ reduce F.lman recurrent curvature.

The structure of the controller used consists of inodifi neural networks that learned on-line by using gcnetic algoritlim teachings.

Using of both front and rear wheels steering simultaneously has automatically controlled the vehicle lateral motion when the vehicle rotates the curvature.

Therefore, it is used a feedback order to control the transient state output of the neural controller that is learned on-line the system by minimizing the error between the actual output of the system and the thm are by model reference output.

The evolutionary techniques based on this a]go ,employed for the model-reference adaptive control scheme for this system