Multi-objective non-fragile static output-feedback control for finite-frequency H∞/GH2 performance in input-delayed active suspension of in-wheel motor electric vehicles

초록

This study addresses a multi-objective control problem for active suspension systems in in-wheel motor-driven electric vehicles (IWM-EVs), considering input delays and gain perturbations as practical implementation uncertainties. A full-vehicle active suspension model is employed to evaluate ride comfort in both the vertical and rotational directions during the design stage. Based on this model, a non-fragile static output-feedback controller is developed to achieve finite-frequency H∞/GH2 performance. Ride comfort is improved by minimizing the finite-frequency H∞ index, while the GH2 index is optimized to enforce safety-related constraints. A static output-feedback structure is adopted to enhance practical implementability, with both input delays and gain perturbations explicitly incorporated into the controller synthesis process. The resulting formulation leads to bilinear matrix inequality (BMI) constraints, which are inherently non-convex due to the static output-feedback design. To address these BMIs and balance conflicting performance objectives, a multi-objective particle swarm optimization algorithm is employed. Simulation results under uneven road conditions demonstrate that the proposed controller improves ride comfort while preserving safety-related performance, even in the presence of uncertainties, thereby providing a robust and practically viable solution for IWM-EV suspension systems. © 2026 Elsevier Ltd.

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