Genetic Algorithm Based PID Controller Tuning Model for Active Suspension System of Self-Driving Vehicle

Abstract

The hunt for a high-performance self-driving vehicle in terms of ride comfort and stability has triggered research into the design, modeling, and simulation of active suspension systems. To maximize the efficiency of a self-driving vehicle's suspension systems in terms of chassis vibration caused by road excitation a simple control mechanism with a high precision level was required. The suspension system's PID controller was tuned using a Genetic Algorithm in this paper. The model was developed and simulated in MATLAB and the results obtained compared with the system without a controller is 33.89% and 95.89% for the settling time and rise time respectively, thereby reducing the body acceleration and suspension travel.