Comfort-Oriented Control for Half-Car Semi-active Suspension Using a Model Predictive Approach

This paper presents a controller design for magnetorheological (MR) semi-active vehicle suspensions, with the main objective of optimizing suspension performance while ensuring that the desired damping coefficients of the front and rear suspension dampers generated by the control law satisfies the physical constraints of the MR damper. To tackle these control objectives, a constrained quadratic programming problem is formulated within the framework of model predictive control (MPC). Integrated Analytic Hierarchy Process (IAHP) and Particle Swarm Optimization (PSO) algorithm are then utilized to optimize the performance of the controller. The optimal control law is determined using the GRAMPC toolbox. Simulation results based on CarSim-MATLAB cosimulations are presented to validate the effectiveness and superiority of the proposed controller compared to conventional control methods.