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Parameter identification and optimization of an oceanographic monitoring remotely operated vehicle

: Rojas, Jorge; Eichhorn, Mike; Baatar, Ganzorig; Matz, Sebastian; Glotzbach, Thomas

Postprint urn:nbn:de:0011-n-5256066 (2.6 MByte PDF)
MD5 Fingerprint: 8c79ed5f5f5aa2d777611123e41109ce
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Erstellt am: 8.1.2019

Institute of Electrical and Electronics Engineers -IEEE-:
OCEANS - MTS/IEEE Kobe Techno-Oceans, OTO 2018 : 28-31 May 2018, Kobe, Japan
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-1654-3
ISBN: 978-1-5386-1653-6
ISBN: 978-1-5386-1655-0
10 S.
Conference "OCEANS - Kobe Techno-Oceans" (OTO) <2018, Kobe>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Remotely operated underwater vehicles (ROV) have become a commonly used platform for many different surveys and the operation of the ROV must be done by highly trained personnel. In order to make the operation of ROVs less complicated and reduce the workload for the operators, it is necessary to have an intelligent control system. The development of an intelligent control system requires an accurate model of an underwater vehicle. However, the necessary parameters within the vehicle model are difficult to determine, especially those concerned with hydrodynamic effects. This paper presents the development of a dynamic and accurate model of an ROV which includes the vehicle motion, gravity, buoyancy effect and the behavior of the vehicle with respect to the forces or moments generated by the thrusters, commanded by the control inputs. An accurate model requires an exact identification of parameters, in order to simulate the real motion of the vehicle. Thus, the main part of this work focuses on hydrodynamic parameter estimation, such as added mass and damping effects, using real underwater motion tests. Due to limitations in the nature of the underwater vehicle not all parameters could be identified. To overcome this problem, an optimization method is performed, which allows to minimize the error between the simulation results and the real motion behavior and thus, to reach an accurate dynamic model of the remotely operated vehicle.