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This paper proposes a robust model predictive control-based solution for therecently introduced series active variable geometry suspension (SAVGS) toimprove the ride comfort and road holding of a quarter car. In order to closethe gap between the nonlinear multi-body SAVGS model and its linear equivalent,a new uncertain system characterization is proposed that captures unmodeleddynamics, parameter variation, and external disturbances. Based on the newlyproposed linear uncertain model for the quarter car SAVGS system, a constrainedoptimal control problem (OCP) is presented in the form of a linear matrixinequality (LMI) optimization. More specifically, utilizing semidefiniterelaxation techniques a state-feedback robust model predictive control (RMPC)scheme is presented and integrated with the nonlinear multi-body SAVGS model,where state-feedback gain and control perturbation are computed online tooptimise performance, while physical and design constraints are preserved.Numerical simulation results with different ISO-defined road events demonstratethe robustness and significant performance improvement in terms of ride comfortand road holding of the proposed approach, as compared to the conventionalpassive suspension, as well as, to actively controlled SAVGS by a previouslydeveloped conventional H-infinity control scheme.

LMI-based robust model predictive control for a quarter car with series active variable geometry suspension