Steering and Speed Control Systems Design for Intelligent Car Using Fuzzy PID Control Algorithm

This study focuses on the Bosiklong F car model, designing and manufacturing an intelligent car specifically for dynamic performance testing on an electromagnetic track. To achieve precise control, an integrated electromagnetic board is used to obtain inductance signals, which are then processed using a Kalman filter for noise suppression and data smoothing. A fuzzy PID control algorithm is applied for differential control of the two-wheel vehicle, and comparative experiments are conducted with traditional PID and cascade PID control algorithms. The experimental results show that the fuzzy PID control algorithm outperforms traditional PID and cascade PID algorithms in terms of speed control stability and response time. By effectively handling system nonlinearity, the fuzzy PID control algorithm improves the car's performance on the electromagnetic track, demonstrating its advantages in complex control environments.