A Fuzzy PID controller applied in AGV control system

With the rapid progress in science and technology, intelligent AGV (Automated Guided Vehicle) is more and more popular in industrial automation. However, since it is very difficult for the traditional proportional-integral-derivative (PID) to strike a balance between the static and dynamic performance of system. In order to make AGV control system more smooth and stable, a fuzzy PID controller to improve the performance of traditional PID control is applied in such system in this paper. Of course, since there are some noise in the physical recognition system, the Kalman filter is also used to reduce the effect of noise. Firstly, on the base of the fuzzy control principle, a fuzzy PID controller is designed, which includes fuzzy language variables, membership function and fuzzy control rules. Secondly, the output fuzzy values through fuzzification, fuzzy control rule and fuzzy decision are fed into conventional PID control system. Thirdly, through the establishment of AGV model, the Kalman filter is utilized to predict the pose of AGV at the next moment by filtering the recognition noise. Finally, simulation results shows its improvement over the conventional PID controller in AGV control system and experiment results of Fuzzy PID with Kalman filter are also given to testify the advantage of the new algorithm.