Abstract
In this paper, a framework for guidance, navigation and control of marine vehicles is proposed. The focus is on application of unmanned surface vehicle for performing high accuracy measuring tasks. The desired maneuvering path is defined as a combination of standard path sections and delivered to the guidance system. The measurements are filtered and the unmeasurable states are estimated in navigation system and fed back to the guidance and control systems. An extended Kalman filter based approach is used in navigation system, in order to take the nonlinear behaviors of the system into consideration. The proposed control scheme is a modular system consisting of a cascade structure, where the unified inner loop is responsible for velocity control and the outer loop can be adapted independently to various missions. The model parameters are estimated based on subspace identification method using data obtained from a measuring vehicle, MESSIN. The results have been further used for design of control and navigation systems. The performance and effectiveness of the proposed framework are demonstrated on a model for a path following mission.
Zusammenfassung
In diesem Beitrag wird ein modularer Framework zur Führung, Navigation und Regelung unbemannter Oberflächenwasserfahrzeuge vorgestellt. Die Manöverplanung wird dem Schiffsführungssystem vorgegeben und fußt auf einer Kombination von verschiedenen Standardtrajektorien. Die Prozessdatenfilterung und -schätzung realisiert ein Navigationssystem, dessen Ausgangsgrößen zur Regelung und Schiffsführung zurück geführt werden. Das Regelungsschema setzt sich aus einer vereinheitlichenden inneren Schleife zur Geschwindigkeitsregelung und einer an die jeweilige Mission zu adaptierende äußeren Regelschleife zur Missionssteuerung zusammen. Die Parameterbestimmung basiert auf Messdaten des unbemannten Oberflächenfahrzeuges MESSIN.
About the authors
Dipl.-Ing. Martin Kurowski is scientist at the Institute of Automation at the University of Rostock. As member of the maritime research group he is responsible for automatic control of marine craft. Main focus lies on automation and control of operational unmanned marine vehicles.
University of Rostock, Institute of Automation, Richard-Wagner-Str. 31, Rostock/Warnemünde, Germany
Dr.-Ing. Adel Haghani received his BSc degree in Electrical Engineering from Sharif University of Technology, Tehran, Iran. He was working with the Institute for Automatic Control and Complex Systems (AKS) of the University of Duisburg-Essen as a PhD student. He is currently with the institute of automation in university of Rostock. His research interests include fault diagnosis and fault tolerant control, process monitoring and asset management.
University of Rostock, Institute of Automation, Richard-Wagner-Str. 31, Rostock/Warnemünde, Germany
M.Sc. Philipp Koschorrek is research assistant at the Institute of Automation at the University of Rostock. After a research stay at Linköping University, Sweden, he started working in Rostock in 2013. He is member of the maritime group with research interests in control and estimation in maritime applications.
University of Rostock, Institute of Automation, Richard-Wagner-Str. 31, Rostock/Warnemünde, Germany
Prof. Dr.-Ing Torsten Jeinsch studied electrical engineering at University of Rostock, Germany and graduated in 1996. After 5 years as research assistant at the Department of Electrical engineering at the Lausitz University of Applied Sciences he moved to the Gasoline Engines Division at IAV GmbH. From 2007 to 2012, he was a Professor of control engineering at the Lausitz University of Applied Science in Senftenberg, Germany. Since 2012, he has been a Professor of control engineering and the head of the Control Application Center (CAC) at the University of Rostock, Germany. His research interests are Software-based Monitoring and fault diagnosis of technical processes with a focus on automotive systems and maritime processes.
University of Rostock, Institute of Automation, Richard-Wagner-Str. 31, Rostock/Warnemünde, Germany
Acknowledgement
The authors want to express their gratitude to the German Federal Ministry of Economics and Technology (BMWi) which has supported this work under Grants DPMotion (No. 03SX351) and SMIS (No. 03SX348).
©2015 Walter de Gruyter Berlin/Boston
