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2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 2521-2528Conference paper, Published paper (Refereed)
Abstract [en]
This paper considers the problem of monitoring and adaptively estimating an environmental field, such as temperature or salinity, using an autonomous underwater vehicle (AUV). The AUV moves in the field and persistently measures environmental scalars and its position in its local coordinate frame. The environmental scalars are approximately linearly distributed over the region of interest, and an adaptive estimator is designed to estimate the gradient. By orthogonal decomposition of the velocity of the AUV, a linear time-varying system is equivalently constructed, and the sufficient conditions on the motion of the AUV are established, under which the global exponential stability of the estimation error system is rigorously proved. Furthermore, an estimate of the exponential convergence rate is given, and a reference trajectory that maximizes the estimate of the convergence rate is obtained for the AUV to track. Numerical examples verify the stability and efficiency of the system.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Adaptive Estimation, Autonomous Underwater Vehicle, Environmental Monitoring, Exponential Stability
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-343722 (URN)10.1109/CDC49753.2023.10383773 (DOI)2-s2.0-85184828866 (Scopus ID)
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023
Note
Part of proceedings ISBN 9798350301243
QC 20240222
2024-02-222024-02-222024-02-29Bibliographically approved