Adaptive control for vehicle model using velocity PID and fuzzy-based delayed resonator for enhanced suspension performance

This study presents an innovative hybrid suspension control architecture that seamlessly integrates a fuzzy-based delayed resonator (DR) and a velocity proportional-integral-derivative (PID) controller to significantly enhance ride comfort and vehicle stability. To ensure dynamic adaptability without excessive computational burden, the system employs a genetic algorithm for optimal parameter tuning and fuzzy logic for real-time supervision. Instead of relying on a single control strategy, the proposed architecture intelligently evaluates physical road excitations: the velocity PID component ensures swift disturbance rejection against acceleration-dominant shocks, while the fuzzy-based delayed resonator effectively eliminates displacement-dominant steady-state errors. Comprehensive simulations demonstrate that this hybrid approach consistently outperforms traditional passive suspensions across various operational scenarios. ± Ultimately, the adaptive synchronisation of these control techniques provides a highly reliable and computationally efficient solution for optimising real-world vehicular dynamics, marking a significant advancement in active suspension technology.