Gain-Scheduled H∞ for Vehicle High-Level Motion Control | Zendy

Moad Kissai | Zendy; Bruno Monsuez | Zendy; Adriana Tapus | Zendy; Xavier Mouton | Zendy; Didier Martinez | Zendy

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Gain-Scheduled H∞ for Vehicle High-Level Motion Control

Author(s) -

Moad Kissai,

Bruno Monsuez,

Adriana Tapus,

Xavier Mouton,

Didier Martinez

Publication year - 2018

Publication title -

hal (le centre pour la communication scientifique directe)

Language(s) - English

Resource type - Conference proceedings

DOI - 10.1145/3284516.3284544

Subject(s) - robustness (evolution) , motion control , computer science , vehicle dynamics , control (management) , control engineering , robust control , reliability (semiconductor) , control theory (sociology) , engineering , control system , automotive engineering , artificial intelligence , robot , biochemistry , chemistry , power (physics) , physics , electrical engineering , quantum mechanics , gene

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.

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