Performance Analysis of Fractionalized Order PID Controller-based on Metaheuristic Optimization Algorithms for Vehicle Cruise Control Systems
Résumé
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 sub optimally under varying conditions. This study introduces a fractionalized-order PID (FrOPID) controller, which incorporates an additional parameter to enhance the performance of conventional PID controllers. 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 in terms of rise time and settling time. Among the proposed designs, the integration of HHO and FrOPID proves to be the most effective in achieving a balance between responsiveness and stability, exhibiting exceptional robustness and adaptability to variations in vehicle mass and environmental conditions. This highlights the effectiveness of fractionalized-order controllers in managing the dynamic behavior of vehicles.
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