Reachability based Model Predictive Control for Semi-active Suspension System

Karthik Murali Madhavan Rathai 1 Olivier Sename 1 Mazen Alamir 2
1 GIPSA-SLR - SLR
GIPSA-DA - Département Automatique
2 GIPSA-SYSCO - SYSCO
GIPSA-DA - Département Automatique
Abstract : This paper proposes a Model Predictive Control (MPC) framework for control of a quarter car semi-active suspension system based on reachable sets approach. The proposed approach provides the flexibility of systematically including the information on the bounds of future road disturbances over the prediction horizon onto the MPC problem formulation by means of reachable sets. This inclusion of future bounds into control design leverages the efficiency of the operation of suspension system. Firstly, a unique Linear Parameter Varying (LPV) model is formulated for control design, which implicitly accounts for the dissipativity constraint of semi-active suspension system. Secondly, an efficient online computation of the reachable sets with the available disturbance information at the current instant for the MPC problem is developed. The proposed methodology is an integration of the preceding steps into a single MPC problem. The effectiveness of the proposed methodology is validated through simulations and the results exhibit better performance of the proposed controller compared to skyhook controller in terms of satisfaction of objective and constraint requirements.
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Communication dans un congrès
Fifth Indian Control Conference 2019, Jan 2019, New Delhi, India
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https://hal.archives-ouvertes.fr/hal-01882534
Contributeur : Karthik Murali Madhavan Rathai <>
Soumis le : jeudi 27 septembre 2018 - 10:27:59
Dernière modification le : vendredi 14 décembre 2018 - 10:08:06
Document(s) archivé(s) le : vendredi 28 décembre 2018 - 12:46:26

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ICC19_0103_MS.pdf
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  • HAL Id : hal-01882534, version 1

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Karthik Murali Madhavan Rathai, Olivier Sename, Mazen Alamir. Reachability based Model Predictive Control for Semi-active Suspension System. Fifth Indian Control Conference 2019, Jan 2019, New Delhi, India. 〈hal-01882534〉

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