An iterative control for driving model based on fuzzy neural network

This paper presented a driver steering controller using an idea of target position. A fuzzy neural system was applied to design the driver´s decision-making process in tracking a target position. A cubic B-spline curve was then employed to generate more flexible paths of lane change to a target position. Additionally, in order to achieve the desired controlling performance, the parameters of the fuzzy neural network were tuned using a new iterative learning control (ILC) mixed time-domain and iteration-domain adaptation. Results from the simulation of the obstacle avoidance show that the tracking error gradually converges to zero as the iteration times increasing.