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Interval Prediction for Continuous-Time Systems with Parametric Uncertainties

Edouard Leurent 1, 2 Denis Efimov 1 Tarek Raissi 3 Wilfrid Perruquetti 1 
1 VALSE - Finite-time control and estimation for distributed systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : The problem of behaviour prediction for linear parameter-varying systems is considered in the interval framework. It is assumed that the system is subject to uncertain inputs and the vector of scheduling parameters is unmeasurable, but all uncertainties take values in a given admissible set. Then an interval predictor is designed and its stability is guaranteed applying Lyapunov function with a novel structure. The conditions of stability are formulated in the form of linear matrix inequalities. Efficiency of the theoretical results is demonstrated in the application to safe motion planning for autonomous vehicles.
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Submitted on : Thursday, November 28, 2019 - 9:49:24 AM
Last modification on : Tuesday, November 22, 2022 - 2:26:16 PM
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Edouard Leurent, Denis Efimov, Tarek Raissi, Wilfrid Perruquetti. Interval Prediction for Continuous-Time Systems with Parametric Uncertainties. 58th IEEE Conference on Decision and Control, Dec 2019, Nice, France. ⟨10.1109/CDC40024.2019.9029480⟩. ⟨hal-02383571⟩



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