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Open AccessArticle

Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles

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Autonomous Systems and Robotics Lab, Computer Science and System Engineering Department (U2IS), École Nationale Supérieure de Techniques Avancées (ENSTA ParisTech), Institut Polytechnique de Paris (IP Paris), 828 Boulevard des Maréchaux, 91120 Palaiseau, France
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Chassis Systems Department, Groupe Renault, 1 Avenue du Golf, 78280 Guyancourt, France
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Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in Kissai, M.; Monsuez, B.; Tapus, A.; Mouton, X.; Martinez, D. Gain-Scheduled H for Vehicle High-Level Motion Control. In Proceedings of the 6th International Conference on Control, Mechatronics and Automation (ICCMA 2018), Tokyo, Japan, 12–14 October 2018; pp. 97–104.
Machines 2019, 7(2), 26; https://doi.org/10.3390/machines7020026
Received: 27 February 2019 / Revised: 14 April 2019 / Accepted: 17 April 2019 / Published: 19 April 2019
Many challenges still need to be overcome in the context of autonomous vehicles. These vehicles would be over-actuated and are expected to perform coupled maneuvers. In this paper, we first discuss the development of a global coupled vehicle model, and then we outline the control strategy that we believe should be applied in the context of over-actuated vehicles. A gain-scheduled H controller and an optimization-based Control Allocation algorithms are proposed. High-fidelity co-simulation results show the efficiency of the proposed control logic and the new possibilities that could offer. We expect that both car manufacturers and equipment suppliers would join forces to develop and standardize the proposed control architecture for future passenger cars. View Full-Text
Keywords: H control; gain scheduling; control allocation; vehicle dynamics; robustness; co-simulation H control; gain scheduling; control allocation; vehicle dynamics; robustness; co-simulation
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Kissai, M.; Monsuez, B.; Mouton, X.; Martinez, D.; Tapus, A. Adaptive Robust Vehicle Motion Control for Future Over-Actuated Vehicles. Machines 2019, 7, 26.

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