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Predictive Control for Trajectory Tracking and Decentralized Navigation of Multi-Agent Formations

Abstract : This paper addresses a predictive control strategy for a particular class of multi-agent formations with a time-varying topology. The goal is to guarantee tracking capabilities with respect to a reference trajectory which is pre-specified for an agent designed as the leader. Then, the rest of the agents, designed as followers, track the position and orientation of the leader. In real-time, a predictive control strategy enhanced with the Potential Field methodology is used in order to derive a feedback control action based only on local information within the group of agents. The main concern is that the interconnections between the agents are time-varying, affecting the neighborhood around each agent. The proposed method exhibits effective performance validated through some illustrative examples.
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https://hal-supelec.archives-ouvertes.fr/hal-00826632
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Submitted on : Monday, March 16, 2020 - 3:53:47 PM
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Ionela Prodan, Sorin Olaru, Cristina Stoica, Silviu-Iulian Niculescu. Predictive Control for Trajectory Tracking and Decentralized Navigation of Multi-Agent Formations. International Journal of Applied Mathematics and Computer Science, University of Zielona Góra 2013, 23 (1), pp.91-102. ⟨10.2478/amcs-2013-0008⟩. ⟨hal-00826632⟩

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