Infinite horizon one-step MPC with linearised constraints for electrically interconnected suspension system

Abstract

This research introduces a novel Infinite Horizon One-Step Model Predictive Control (IHOS-MPC) algorithm with linearised constraints, specifically designed for semi-active Electrically Interconnected Suspension (EIS) systems to enhance vehicle dynamics and comfort. The proposed control approach combines an infinite predictive horizon with a control horizon of one, significantly reducing computational complexity while maintaining efficient, real-time control performance. By integrating linearised constraints, the algorithm operates within feasible limits, minimizing computational overhead without compromising control quality. The EIS system employs electromagnetic dampers consisting of direct current motors, allowing real-time adjustments to optimise damping forces and address both vertical and roll dynamics of the vehicle. Experimental validation demonstrates that the system effectively handles various road conditions, achieving notable improvements in ride comfort and stability. This study establishes the practicality and effectiveness of the IHOS-MPC with linearised constraints in real-world applications, offering a compelling solution for advancing semi-active suspension systems in modern vehicles.