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The anti-lock brake system (ABS) is a vital system in modern vehicles that prevents automotive wheels from locking during an emergency brake. This paper aims to introduce an efficient, optimized proportional integral derivative (PID) controller tuned using a genetic algorithm (GA) to enhance the performance of ABS. The PID control method is a very famous control algorithm employed in numerous engineering applications. The GA is used to solve the nonlinear optimization problem and search for the optimum PID controller gains by identifying the solution to the problem. A mathematical model of ABS is derived and simulated using Matlab and Simulink software. The proposed optimized PID-controlled ABS is compared to the conventional ABS controlled using a Bang-Bang controller. System performance criteria are evaluated and assessed under different road adhesion coefficient values to judge the success of the proposed PID controller tuned using GA.

In order to achieve the high capability of the ride comfort and regulating the tire slip ratio, a preview of a nonlinear semi-active vibration control suspension system using a magnetorheological (MR) fluid damper is integrated with traction control in this paper. A controlled semi-active suspension system, which consists of the system controller and damper controller, was used to develop ride comfort, while the traction controller is utilized to reduce a generated slip between the vehicle speed and rotational rate of the tire. Both Fractional-Order Filtered Proportional-Integral-Derivative (P¯IλDμ) and Fuzzy Logic connected either series or parallel with P¯IλDμ are designed as various methodologies of a system controller to generate optimal tracking of the desired damping force. The signum function method is modified as a damper controller to calculate an applied input voltage to the MR damper coil based on both preview signals and the desired damping force tracking.