LMI-based robust model predictive control for a quarter car with series active variable geometry suspension
Zilin Feng, Anastasis Georgiou, Simos A. Evangelou, Min Yu, Imad M, Jaimoukha, Daniele Dini

TL;DR
This paper introduces a robust model predictive control method based on linear matrix inequalities for a quarter car with a series active variable geometry suspension, enhancing ride comfort and road holding under various road conditions.
Contribution
It develops a new uncertain system model for SAVGS that captures unmodeled dynamics and disturbances, and integrates an LMI-based RMPC scheme with the nonlinear system for improved control.
Findings
Demonstrates robustness against unmodeled dynamics and disturbances.
Achieves significant performance improvements over passive and H-infinity controlled SAVGS.
Validates effectiveness through numerical simulations with ISO road events.
Abstract
This paper proposes a robust model predictive control-based solution for the recently introduced series active variable geometry suspension (SAVGS) to improve the ride comfort and road holding of a quarter car. In order to close the gap between the nonlinear multi-body SAVGS model and its linear equivalent, a new uncertain system characterization is proposed that captures unmodeled dynamics, parameter variation, and external disturbances. Based on the newly proposed linear uncertain model for the quarter car SAVGS system, a constrained optimal control problem (OCP) is presented in the form of a linear matrix inequality (LMI) optimization. More specifically, utilizing semidefinite relaxation 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…
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Taxonomy
TopicsVehicle Dynamics and Control Systems · Vibration Control and Rheological Fluids · Electric and Hybrid Vehicle Technologies
