Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers
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...
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| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Machines |
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| Online Access: | https://www.mdpi.com/2075-1702/13/6/512 |
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| author | Fernando Viadero-Monasterio Miguel Meléndez-Useros Manuel Jiménez-Salas María Jesús López Boada |
| author_facet | Fernando Viadero-Monasterio Miguel Meléndez-Useros Manuel Jiménez-Salas María Jesús López Boada |
| author_sort | Fernando Viadero-Monasterio |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-6a4ee64fedc84fc39d8d939aa202f5ce |
| institution | OA Journals |
| issn | 2075-1702 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machines |
| spelling | doaj-art-6a4ee64fedc84fc39d8d939aa202f5ce2025-08-20T02:21:04ZengMDPI AGMachines2075-17022025-06-0113651210.3390/machines13060512Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological DampersFernando Viadero-Monasterio0Miguel Meléndez-Useros1Manuel Jiménez-Salas2María Jesús López Boada3Mechanical Engineering Department, Advanced Vehicle Dynamics and Mechatronic Systems (VEDYMEC), Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, SpainMechanical Engineering Department, Advanced Vehicle Dynamics and Mechatronic Systems (VEDYMEC), Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, SpainMechanical Engineering Department, Advanced Vehicle Dynamics and Mechatronic Systems (VEDYMEC), Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, SpainMechanical Engineering Department, Advanced Vehicle Dynamics and Mechatronic Systems (VEDYMEC), Universidad Carlos III de Madrid, Avda. de la Universidad 30, 28911 Leganés, SpainThis 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.https://www.mdpi.com/2075-1702/13/6/512semi-active suspensionmagnetorheological dampervehicle dynamicsvehicle safetyride comfortintelligent transportation system |
| spellingShingle | Fernando Viadero-Monasterio Miguel Meléndez-Useros Manuel Jiménez-Salas María Jesús López Boada Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers Machines semi-active suspension magnetorheological damper vehicle dynamics vehicle safety ride comfort intelligent transportation system |
| title | Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers |
| title_full | Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers |
| title_fullStr | Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers |
| title_full_unstemmed | Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers |
| title_short | Avoiding Lyapunov-Krasovskii Functionals: Simple Nonlinear Sampled–Data Control of a Semi-Active Suspension with Magnetorheological Dampers |
| title_sort | avoiding lyapunov krasovskii functionals simple nonlinear sampled data control of a semi active suspension with magnetorheological dampers |
| topic | semi-active suspension magnetorheological damper vehicle dynamics vehicle safety ride comfort intelligent transportation system |
| url | https://www.mdpi.com/2075-1702/13/6/512 |
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