Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers - Fernando Viadero-Monasterio; Miguel Meléndez-Useros; Manuel Jiménez-Salas; María Jesús López Boada (Machines)
This paper presents a novel control design methodology for a magnetorheological (MR) damper-based semi-active suspension system operating under communication-induced time delays, which introduce nonlinear sampled-data dynamics. To address these challenges, a linear matrix inequality (LMI) framework is developed for synthesizing the current controller, with the dual goals of enhancing ride comfort and safety while ensuring system stability and robustness against road disturbances. The proposed approach deliberately avoids the use of Lyapunov-Krasovskii functionals, offering a more practical and computationally efficient alternative. Experimental results confirm that the proposed MR damper model outperforms traditional Lyapunov-Krasovskii-based methods. Additionally, two simulated road profiles are used to evaluate the suspension system’s behavior, further demonstrating the effectiveness of the proposed control strategy.