Improved Differential Steering Control Algorithm for Intelligent Vehicles

Differential steering control for intelligent vehicles is one of the key technologies in automated control. Existing methods employ PID control for differential steering; however, these methods often suffer from speed fluctuations and poor stability. Therefore, we propose an improved differential control algorithm. By analyzing the current state and error information of the vehicle, we dynamically adjust the vehicle's speed using fuzzy control logic combined with differential proportional control, thereby enhancing the vehicle's stability and response speed in complex environments. Experimental results show that, compared to traditional PID control, this method effectively reduces speed fluctuations and improves the motion accuracy of the vehicle in nonlinear environments.