Anti-lock braking system control algorithm for driverless mining dump truck based on fuzzy PID

This paper focuses on mining dump trucks and designs an Anti-lock Braking System (ABS) control algorithm based on estimating road surface adhesion conditions. In the estimation of road adhesion conditions, in order to solve the problem that the traditional recursive algorithm is complicated to estimate the time-varying parameters accurately, this paper designs an adhesion condition estimation method based on the least recursive quadratic method with forgetting factor, which improves the identification accuracy of peak adhesion coefficient and optimal slip ratio. The fuzzy PID algorithm is used to design the ABS control strategy based on the optimal slip ratio control principle and fuzzy control theory. The ABS control strategy simulation test is carried out with the help of the MATLAB/Simulink simulation platform. The real vehicle test of the control algorithm is completed on a driverless mining dump truck. The results of real vehicle tests indicate that, compared to the traditional logic threshold algorithm, the ABS control strategy based on parameter self-tuning fuzzy PID control more effectively enhances the braking performance and handling stability of the mining truck during emergency braking and significantly reduces the braking distance.