Comparative Analysis of Fuzzy Controllers in a Truck Cruise Control System

The paper considers the problem of improving the cruise control system used to control the speed of a truck. It is proposed to supplement the existing control system with a supervisor that adjusts the parameters of the classic PID controller in real time depending on the current state and driving modes of the vehicle. To ensure effective work of the supervisor in conditions of incompleteness and inaccuracy of incoming information, it is proposed to use fuzzy logic methods. Three most frequently used variants of the fuzzy supervisor implementation are considered: the PID controller coefficients are calculated by the supervisor based on the error signal, the PID controller coefficients are adjusted by the supervisor based on the error signal, the PID controller coefficients are calculated by the supervisor based on the difference between the output of the control system and the reference model. The parameters of the PID controller and the fuzzy supervisor are adjusted to ensure the minimum value of the transition process time. For each of the considered variants, the results of computer modeling of the processes of changing the speed of a truck are presented. The most effective algorithm for controlling the speed of a truck is proposed, as well as directions for further improvement of the cruise control system.