Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions

A. L. Do, B. Soualmi, J. Lozoya-Santos, O. Sename, L. Dugard, R. Ramirez-Mendoza

Research output: Contribution to conferencePaper

3 Citations (Scopus)

Abstract

Multi-objective optimization is a popular problem in engineering design. In semi-Active suspension control, comfort and road holding are two essential but conflicting performance objectives. In a previous work, the authors proposed an LPV formulation for semi-Active suspension control of a realistic nonlinear suspension model where the nonlinearities (i.e the bi-viscous and the hysteresis) have been taken into account; an H∞/LPV controller to handle the comfort and road holding has been also designed. The present paper aims at improving the method of [6] by using Genetic Algorithms (GAs) to select the optimal weighting functions for the H∞/LPV synthesis. First, a general procedure for the optimization of weighting function for the H∞/LPV synthesis is proposed and then applied to the semi-Active suspension control. Thanks to GAs, the comfort and road holding conflicting objectives are handled using a single high level parameter and illustrated via the Pareto optimality. The simulation results performed on a nonlinear vehicle model emphasize the efficiency of the method.
Original languageEnglish
Pages471-484
Number of pages14
Publication statusPublished - 1 Jan 2010
Externally publishedYes
EventProceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies -
Duration: 1 Jan 2010 → …

Conference

ConferenceProceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies
Period1/1/10 → …

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Genetic algorithms
Control nonlinearities
Multiobjective optimization
Hysteresis
Controllers

Cite this

Do, A. L., Soualmi, B., Lozoya-Santos, J., Sename, O., Dugard, L., & Ramirez-Mendoza, R. (2010). Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions. 471-484. Paper presented at Proceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies, .
Do, A. L. ; Soualmi, B. ; Lozoya-Santos, J. ; Sename, O. ; Dugard, L. ; Ramirez-Mendoza, R. / Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions. Paper presented at Proceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies, .14 p.
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Do, AL, Soualmi, B, Lozoya-Santos, J, Sename, O, Dugard, L & Ramirez-Mendoza, R 2010, 'Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions', Paper presented at Proceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies, 1/1/10 pp. 471-484.

Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions. / Do, A. L.; Soualmi, B.; Lozoya-Santos, J.; Sename, O.; Dugard, L.; Ramirez-Mendoza, R.

2010. 471-484 Paper presented at Proceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies, .

Research output: Contribution to conferencePaper

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AU - Sename, O.

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AB - Multi-objective optimization is a popular problem in engineering design. In semi-Active suspension control, comfort and road holding are two essential but conflicting performance objectives. In a previous work, the authors proposed an LPV formulation for semi-Active suspension control of a realistic nonlinear suspension model where the nonlinearities (i.e the bi-viscous and the hysteresis) have been taken into account; an H∞/LPV controller to handle the comfort and road holding has been also designed. The present paper aims at improving the method of [6] by using Genetic Algorithms (GAs) to select the optimal weighting functions for the H∞/LPV synthesis. First, a general procedure for the optimization of weighting function for the H∞/LPV synthesis is proposed and then applied to the semi-Active suspension control. Thanks to GAs, the comfort and road holding conflicting objectives are handled using a single high level parameter and illustrated via the Pareto optimality. The simulation results performed on a nonlinear vehicle model emphasize the efficiency of the method.

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Do AL, Soualmi B, Lozoya-Santos J, Sename O, Dugard L, Ramirez-Mendoza R. Optimization of weighting function selection for H<inf>∞</inf>control of semi-Active suspensions. 2010. Paper presented at Proceedings of the Mini Conference on Vehicle System Dynamics, Identification and Anomalies, .