@inproceedings{7360f1924bf1487db29568c1e8ee2a47,
title = "Model Predictive Control Allocation of Systems with Different Dynamics",
abstract = "Several systems are integrated in passenger cars. Some of them are just redundant systems due to safety requirements. Others, are completely different and can interact with each other as long as they are operating inside the same vehicle. Control allocation methods have been successfully implemented in advanced aircrafts to avoid conflicts, especially in the context of redundant systems. In this paper, we will rather focus on coordinating non-redundant advanced chassis systems with different dynamics. This difference in dynamics can be especially problematic when systems exhibit different communication delays. Model Predictive Control Allocation (MPCA) methods are therefore investigated in order to activate the right system at the right moment. Results show that particularly when the most effective system is saturated, another system with a different time delay can be activated few steps before saturation to instantly take over the maneuver. With good knowledge of actuator dynamics and higher computation power, MPCA methods are able to solve complex problems in severe situations.",
keywords = "Chassis Systems, Identification, Model Predictive Control Allocation, Robust Control, Vehicle Dynamics",
author = "Moad Kissai and Bruno Monsuez and Xavier Mouton and Didier Martinez and Adriana Tapus",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 ; Conference date: 27-10-2019 Through 30-10-2019",
year = "2019",
month = oct,
day = "1",
doi = "10.1109/ITSC.2019.8917438",
language = "English",
series = "2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4170--4177",
booktitle = "2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019",
}