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Consensus of Double-Integrator Multi-Agent Systems Using Decentralized Model Predictive Control

Abstract : This paper studies the consensus for a group of agents which have a discrete-time double-integrator dynamics. To solve this problem, a Model Predictive Control (MPC) scheme is introduced. The proposed control protocol is decentralized and is designed by combining graph theory with a predictive control algorithm to take into account the switches on the communication topology. The predictive strategy is used to estimate input and output of agent through a receding horizon. Contrary to many existing works, the cost function is designed using the difference between two consecutive inputs. The controller has integrator properties to eliminate steady-state errors. Finally, some simulation results are given to show the effectiveness of the proposed model predictive control.
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https://hal-uphf.archives-ouvertes.fr/hal-03411400
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Submitted on : Tuesday, November 2, 2021 - 11:23:43 AM
Last modification on : Wednesday, November 3, 2021 - 3:53:01 AM

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  • HAL Id : hal-03411400, version 1

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Pipit Anggraeni, Michael Defoort, Mohamed Djemai, Aries Subiantoro, Abdul Muis. Consensus of Double-Integrator Multi-Agent Systems Using Decentralized Model Predictive Control. 5th International Conference on Control Engineering and Information Technology, Dec 2017, Sousse, Tunisia. ⟨hal-03411400⟩

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