Model Predictive Control of Autonomous Vehicles

Abstract : The control of autonomous vehicles is a challenging task that requires advanced control schemes. Nonlinear Model Predictive Control (NMPC) and Moving Horizon Estimation (MHE) are optimization-based control and estimation techniques that are able to deal with highly nonlinear, constrained, unstable and fast dynamic systems. In this chapter, these techniques are detailed, a descriptive nonlinear model is derived and the performance of the proposed control scheme is demonstrated in simulations of an obstacle avoidance scenario on a low-fricion icy road.
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Chapitre d'ouvrage
Harald Waschl and Ilya Kolmanovsky and Maarten Steinbuch and Luigi del Re. Optimization and Optimal Control in Automotive Systems, 455, Springer, pp.41-57, 2014, Lecture Notes in Control and Information Sciences, 〈10.1007/978-3-319-05371-4_3〉
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https://hal.inria.fr/hal-01068524
Contributeur : Estelle Bouzat <>
Soumis le : jeudi 25 septembre 2014 - 17:15:22
Dernière modification le : lundi 21 mars 2016 - 11:30:33

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Mario Zanon, Janick V. Frasch, Milan Vukov, Sebastian Sager, Moritz Diehl. Model Predictive Control of Autonomous Vehicles. Harald Waschl and Ilya Kolmanovsky and Maarten Steinbuch and Luigi del Re. Optimization and Optimal Control in Automotive Systems, 455, Springer, pp.41-57, 2014, Lecture Notes in Control and Information Sciences, 〈10.1007/978-3-319-05371-4_3〉. 〈hal-01068524〉

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