Research Of Pilot PID Control Model Based On Intelligent Control Technology

With the increasing of cars, traffic accidents frequently occur, the growing traffic safety concerned. By improving the vehicle's intelligence program is the best choice to achieve security and efficient autopilot. At the same time, it also can lay the foundation of the intelligent vehicle which runs to the developing well-automatic high-speed traffic network environment in the future. That is why the needing for appropriate driver model, which handles the traffic condition and the perception of the information timely and accurately, controls the output of vehicles accurately, and achieves automatic driving.This paper describes fuzzy neural system and a single neuron self-adaptive PID control combined with the realization of automatic vehicle driving. The basic design and implementation procedure is as following: First, describing driving behaviors of a human driver under various situations using fuzzy logic-based rules. Improving the driving performance using neural networks specifically conduction according to the fuzzy driving rules. In this way, the low cost control implementation and the complexity of learning algorithm can be integrated effective, and the structure of fuzzy neural controller is based on the method. Second, using analog exercise control of the driver behavior model of single neuron, sets up an auto direction of single neuron self-adaptive PID controller, and achieves control parameters of the traditional auto direction PID controller tuning online. Finally, fuzzy neural controller and PID controller in parallel together to form composite control model, which verifies the effectiveness and feasibility of the model by lane keeping control simulation on the analog traffic, and gives a preferable solution to the automatic drive on the empty way.The innovation lies in using of driver behavior imitation of fuzzy neural network technology and the traditional PID control technology fitted to establish a composite control model. The model ensures the accuracy of control and self-adaptive, it also reflects the good behavior of the driver and makes crew have a good acceptance on the lane keeping system, for automotive driver assistance systems to provide a viable control of humanoid Methods.