@article{5a2c8b1aed0b49f9be2522b72a5465f9,
title = "Receding horizon control and coordination of multi-agent systems using polynomial expansion",
abstract = "The present paper proposes a flexible and efficient methodology for constructing norm-bounded optimal receding horizon control laws for a group of agents, each one of which is described as a repeated integrator of an arbitrary order and with a common input delay. The goal of each agent is to track the given target, while simultaneously avoiding other agents in the group. Polynomial expansion, together with appropriate subspace projection, is utilized in order to derive receding control law in the closed form. Properties of this control law have been investigated, and its link to a well-known control strategy based on avoidance functions, which ensures collision avoidance in the case of first-order integrator agents, has been derived.",
author = "Rapai{\'c}, {Milan R.} and Kapetina, {Mirna N.} and Stipanovi{\'c}, {Du{\v s}an M.}",
note = "Funding Information: This work is supported by grant no. 451‐03‐68/2020‐14/200156, titled “Innovative Scientific and Artistic Research from the FTS (activity) Domain,” from the Ministry of Education, Science and Technological Development of the Republic of Serbia (Ministarstvo prosvete, nauke i tehnolo{\v s}kog razvoja) and the National Robotics Initiative grant titled “NRI: FND:COLLAB: Multi‐Vehicle Systems for Collecting Shadow‐Free Imagery in Precision Agriculture” (grant no. 2019‐04791/project accession no. 1020285) from the USDA National Institute of Food and Agriculture. Publisher Copyright: {\textcopyright} 2022 Chinese Automatic Control Society and John Wiley & Sons Australia, Ltd",
year = "2022",
doi = "10.1002/asjc.2732",
language = "English (US)",
journal = "Asian Journal of Control",
issn = "1561-8625",
publisher = "National Taiwan University (IEEB)",
}