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Attainable-Set Model Predictive Control for AUV Formation Control

Title
Attainable-Set Model Predictive Control for AUV Formation Control
Type
Article in International Conference Proceedings Book
Year
2018
Authors
Rui Gomes
(Author)
Other
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Conference proceedings International
Pages: 1-6
2018 IEEE/OES Autonomous Underwater Vehicle Workshop, AUV 2018
6 November 2018 through 9 November 2018
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Publicação em ISI Web of Science ISI Web of Science
Publicação em Scopus Scopus - 0 Citations
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Other information
Authenticus ID: P-00Q-SCP
Resumo (PT):
Abstract (EN): In this article, we focus on the motion control of an AUV formation in order to track a given path along which data will be gathered. A computationally efficient architecture enables the conciliation of onboard resources optimization with state feedback control-to deal with the typical a priori high uncertainty-while managing the formation with a low computational and power budgets. To meet these very strict requirements, a novel Model Predictive Control (MPC) scheme is used. The key idea is to pre-compute data which is known to be time invariant for a number of likely scenarios and store it on-board in appropriate look-up tables. Then, as the mission proceeds, sampled motion sensor data, and communicated data is processed in each one of the AUVs and fed to the onboard proposed MPC scheme implemented with the dynamics of the formation that, by combining with information extracted from the pertinent on-board look-up tables, determine the best control action with inexpensive computational operations. © 2018 IEEE.
Language: English
Type (Professor's evaluation): Scientific
No. of pages: 6
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