Constrained Model Predictive Control for Time-Varying Delays Systems: Application to an Active Car Suspension

dc.contributor.authorS. Bououden, M. Chadli, L. Zhang and T. Yang,
dc.date.accessioned2024-02-15T15:25:47Z
dc.date.available2024-02-15T15:25:47Z
dc.date.issued2016
dc.description.abstractThis study investigates the problem of robust model predictive control (RMPC) for active suspension systems with time-varying delays and input constraints. The uncertainty is of convex polytopic type. Based on the Lyapunov-Krasovskii functional method, sufficient stability conditions of the time-varying delays systems are derived by linear matrix inequalities (LMIs) terms. At each time set, a feasible state feedback is obtained by minimizing an upper bound of the ‘worst-case’ quadratic objective function over an infinite horizon subject to constraints on inputs. Finally, a quarter-vehicle model is exploited to demonstrate the effectiveness of the proposed method.
dc.identifier.urihttp://dspace.univ-khenchela.dz:4000/handle/123456789/1233
dc.language.isoen_US
dc.publisherInternational Journal of Control, Automation and Systems, Springer
dc.titleConstrained Model Predictive Control for Time-Varying Delays Systems: Application to an Active Car Suspension
dc.typeArticle
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