Optimized Fuzzy Control Algorithm for Motion Control of a Four-Wheeled Differential Robot

In order to address the situation of wheel slip in wheeled mobile robot under linear motion state, a speed control strategy based on genetic algorithm optimized fuzzy proportional, integral and differential (PID) controller is proposed in this article. Through establishment of the wheeled mobile robot inverse kinematics model, the motion state analysis on the four-wheel differential wheeled robot with wheel slipping is carried out, the fuzzy PID controller and robot control strategy based on the genetic algorithm optimization are designed. Two main slipping conditions affecting linear motion are selected for simulation and experimental analysis. Through the analysis, it is shown that compared to the traditional PID control, the overall acceleration response time of the control strategy is reduced by 0.58 s, and the overshoot amount is less than 1.5%. The results show that the convergence speed and stability of the control strategy have achieved a more significant improvement, which verifies the effectiveness of the method, solves the slipping problem of the wheeled mobile robot, and realizes the goal of accuracy, timeliness and robustness of the motion control.