Intelligent Car Trajectory Tracking Method Based on Feedforward Variable Domain Fuzzy PID Control

In order to improve the accuracy and anti-interference ability of intelligent car trajectory tracking, a fuzzy control method based on feedforward variable domain was proposed. Taking the automated guided vehicle (AGV) as the research object, the kinematic model of the car was established to conduct the dynamic analysis on it. Under the condition of keeping the main control parameters unchanged, the feedforward control was added into the variable-theoretic domain fuzzy control to build the feedforward variable-theoretic domain fuzzy PID control system, and the parameters were adjusted through the variable domain fuzzy PID control to achieve better stability. Then the system achieved optimal target tracking performance by the adjusting the feedforward control parameters. An S-shaped curve tracking route was set up and the simulation experiments on four control models, including traditional PID, fuzzy PID, variable universe fuzzy PID, and feedforward variable domain fuzzy PID were conducted on the Matlab/Simulink platform to compare and verify the control performance of the proposed method. The results show that under the condition of no interference, the maximum lateral deviation of vehicle turning of the four control methods is 0.258 0, 0.198 8, 0.179 2 and 0.112 5 m, respectively, and the method proposed in this paper has the smallest deviation and the highest trajectory tracking accuracy. Under the simulated real road conditions, the maximum lateral deviation of vehicle turning of the four control methods is 0.891 7, 0.820 9, 0.791 7, 0.683 3 m, respectively. The deviation of the proposed method is still the smallest, and the anti-interference ability is the strongest, which confirms that the control method proposed in this paper has the advantages of high tracking precision and excellent stability.