Controller design for adaptive cruise control system based on electric charged particles optimization algorithm.

Adaptive Cruise Control (ACC) systems are widely used in modern vehicles to enhance driving comfort and safety. The design of an effective controller for ACC is crucial for achieving smooth and efficient vehicle following behavior. In this paper, the mathematical model of the normal linear system and the adaptive cruise control system (ACCS) of the electric vehicle (EV) are developed. Consequently, these systems are simulated using Matlab to analyze the output responses of the system before being controlled. Additionally, the proportional-integral-Derivative (PID) control is designed to compensate for the performance of the developed EV systems to get a better response. After that, a new optimization method is applied to tune the PID controller parameters known as "electric charged particle optimization" (ECPO). Additionally, the simulated outcomes for both PID-controlled systems are displayed in the result section. The effectiveness of the suggested controller and the new optimization method are then compared. Additionally, using the reference input, the tracking of the ACC electric car system has been achieved at 98%. [ABSTRACT FROM AUTHOR]