Performance Analysis of Fractionalized Order PID Controller-based on Metaheuristic Optimisation Algorithms for Vehicle Cruise Control Systems

Abstract

Recently, automotive manufacturers have prioritized cruise control systems and controllers, recognizing them as essential components requiring precise and adaptable designs to keep up with technological advancements. The motion of vehicles is inherently complex and variable, leading to significant non-linearity within the cruise control system (CCS). Due to this non-linearity, conventional PID controllers often perform suboptimally under varying conditions. This research introduces a fractionalized-order PID (FrOPID) controller, which has an extra parameter that makes regular PID controllers work better. A comparative analysis is conducted between classical PID controllers and FrOPID controllers optimized using three metaheuristic algorithms: Harris Hawks Optimization (HHO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). The evaluation is carried out using a linearized model of the vehicle cruise control system (VCCS). The results demonstrate that fractionalized-order PID controllers significantly outperform conventional PID controllers, particularly regarding rise time and settling time. Among the designs that were considered, the one that combines HHO and FrOPID works the best at finding a balance between responsiveness and stability. It is also the most durable and flexible, able to adapt to changes in vehicle mass and environmental conditions. This highlights the effectiveness of fractionalized-order controllers in managing the dynamic behavior of vehicles.