Fuzzy Neural Pid Used In Smart Car Pursuit And Obstacle Avoidance Control

Intelligent robot has a wide use in the fields of military detection, aerospace, EOD danger, industrial production and people's daily life. The most intelligent performances of mobile robot are robot's behavior control and its capabilities of pursuing goals and avoid obstacles. The research on robot's ability to pursuit goals and avoid obstacles are very useful to the safe operation of smart car and unmanned aircraft. The algorithm of pursuing goals and avoiding obstacles is the key of a smart car to pursuit goals and avoid obstacles. Some of the traditional control algorithms often depend on the precise controlled object model and fully known environmental information. When the control object is relatively complex, and there are more control parameters or unknown environmental information, and the accurate mathematical model is difficult to establish, the effect of the traditional control algorithms are often unsatisfactory.As a result of the above situations, this article brought up a new control algorithm—Fuzzy Neural PID Control algorithm. This algorithm combines the advantages of fuzzy control theory, neural network control and PID control. The key of this method is how to use the neural network to describe the rules of fuzzy control, in this article, we solved this problem.This article introduced how did the car obtain the information of external environment, how to process the data that obtained, and then we designed the algorithm of pursuing goals and avoiding obstacles, according to the smart car--a production of Shanghai Ingenious Automation Co., Ltd.The algorithm can be divided into goal pursuit mode and obstacle avoidance mode, in certain conditions this two modes are interchangeable. The algorithms of the two modes are to control the steering angle of the car, making the car move closer to the target point and when in the face of obstacles can judge for themselves whether to take avoidance measures.In the last of this article we used Matlab toolbox to simulate the fuzzy neural PID control on the algorithm of pursuit goals and avoid obstacles of the smart car. Also we compared the separate PID control with fuzzy control, the result shows that this new method has an effective way.