@inproceedings{d81923ee11eb43b6a185940246eba73f,
title = " Gain-scheduled H ∞ for vehicle high-level motion control ",
abstract = "Vehicle motion control has many challenges to overcome. One of the main problems is robustness against not only environmental changes but also uncertainties about the vehicle itself. This paper focuses on this problem using robust control design at the control architecture's high level. Researches tend to decentralize the control to treat longitudinal and lateral dynamics separately. Here, an overall vehicle model is first proposed and studied to justify the structure that the high-level controller should embrace. Co-simulation results of different combinations showed promising performances to face uncertainties and couplings. Therefore, robust techniques combined with control allocation techniques may enhance autonomous vehicles reliability.",
keywords = "Co-Simulation, Control Allocation, Gain Scheduling, H∞ Control, Robustness, Vehicle Dynamics",
author = "Moad Kissai and Bruno Monsuez and Adriana Tapus and Xavier Mouton and Didier Martinez",
note = "Publisher Copyright: {\textcopyright} 2018 ACM.; 6th International Conference on Control, Mechatronics and Automation, ICCMA 2018 ; Conference date: 12-10-2018 Through 14-10-2018",
year = "2018",
month = oct,
day = "12",
doi = "10.1145/3284516.3284544",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "97--104",
booktitle = "ICCMA 2018 - Proceedings of the 6th International Conference on Control, Mechatronics and Automation",
}