Towards improved AUV control through learning of periodic signals

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Title: Towards improved AUV control through learning of periodic signals
Authors: Kormushev, P
Caldwell, DG
Item Type: Conference Paper
Abstract: Designing a high-performance controller for an Autonomous Underwater Vehicle (AUV) is a challenging task. There are often numerous requirements, sometimes contradicting, such as speed, precision, robustness, and energy-efficiency. In this paper, we propose a theoretical concept for improving the performance of AUV controllers based on the ability to learn periodic signals. The proposed learning approach is based on adaptive oscillators that are able to learn online the frequency, amplitude and phase of zero-mean periodic signals. Such signals occur naturally in open water due to waves, currents, and gravity, but can also be caused by the dynamics and hydrodynamics of the AUV itself. We formulate the theoretical basis of the approach, and demonstrate its abilities on synthetic input signals. Further evaluation is conducted in simulation with a dynamic model of the Girona 500 AUV on a hovering task.
Issue Date: 30-Sep-2013
Date of Acceptance: 23-Sep-2013
URI: http://hdl.handle.net/10044/1/26080
Publisher: IEEE
Start Page: 1
End Page: 4
Journal / Book Title: Proc. MTS/IEEE Intl Conf. OCEANS 2013
Copyright Statement: © 2013 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Conference Name: OCEANS 2013
Publication Status: Published
Publisher URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6741187
Start Date: 2013-09-23
Finish Date: 2013-09-27
Conference Place: San Diego, CA
Appears in Collections:Dyson School of Design Engineering



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