Navigation and Automatic Control of the Measuring Dolphin (Messin™)

Majohr, Jürgen; Buch, Thomas; Korte, Cathleen

doi:10.1016/s1474-6670(17)37107-0

Cited by 19 publications

(10 citation statements)

References 1 publication

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“…bathymetry, pollution monitoring, etc. European prototypes include the Measuring Dolphin (MESSIN), developed by the University of Rostock, Germany (Majohr et al, 2000) and the autonomous catamaran, Charlie, from The Institute of Intelligent Systems for Automation, Genova, Italy. Charlie is a catamaran shaped prototype vessel which has been used to gather sea surface samples during the XIX Italian expedition to Antarctica (Bibuli et al, 2008).…”

Section: Research Vessel Prototypesmentioning

confidence: 99%

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

Campbell

Naeem

Irwin

2012

Annual Reviews in Control

406

176

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Section: Research Vessel Prototypesmentioning

confidence: 99%

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

Campbell

Naeem

Irwin

2012

Annual Reviews in Control

406

176

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“…From the review by Motwani, 1 it is clear that unmanned surface vehicles (USVs) are now being used in an array of different application areas in the commercial, naval and scientific sectors. Indeed, they are currently being used for mine counter-measures, 2 surveying 3 and environmental data gathering, 4 to name but a few. In order to meet the ongoing challenges of these sectors USV technology continues to be developed particularly in the field of navigation, guidance and control systems.…”

Section: Introductionmentioning

confidence: 99%

Non-linear control algorithms for an unmanned surface vehicle

Sharma

Sutton

Motwani

2013

Proceedings of the Institution of Mechanical Engineers, Part M:

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Although intrinsically marine craft are known to exhibit non-linear dynamic characteristics, modern marine autopilot system designs continue to be developed based on both linear and non-linear control approaches. This article evaluates two novel non-linear autopilot designs based on non-linear local control network and non-linear model predictive control approaches to establish their effectiveness in terms of control activity expenditure, power consumption and mission duration length under similar operating conditions. From practical point of view, autopilot with less energy consumption would in reality provide the battery-powered vehicle with longer mission duration. The autopilot systems are used to control the non-linear yaw dynamics of an unmanned surface vehicle named Springer. The yaw dynamics of the vehicle being modelled using a multi-layer perceptron-type neural network. Simulation results showed that the autopilot based on local control network method performed better for Springer. Furthermore, on the whole, the local control network methodology can be regarded as a plausible paradigm for marine control system design.

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“…Indeed they are now used for mine counter-measures (Yan et al, 2010), surveying (Majohr et al, 2000) and environmental data gathering (Caccia, 2007), to name just three.…”

Section: Introductionmentioning

confidence: 99%

An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

2012

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Over recent years, a number of marine autopilots designed using linear techniques have underperformed owing to their inability to cope with nonlinear vessel dynamics. To this end, a new design framework for the development of nonlinear autopilots is proposed. Local Control Networks (LCNs) can be used in the design of nonlinear control systems. In this paper, a LCN approach is taken in the design of a nonlinear autopilot for controlling the nonlinear yaw dynamics of an unmanned surface vehicle known as Springer. It is considered the approach is the first of its kind to be used in marine control systems design. Simulation results are presented and the performance of the nonlinear autopilot is compared with that of an existing Springer Linear Quadratic Gaussian (LQG) autopilot using standard system performance criteria. From the results it can be concluded the LCN autopilot out-performed that based on LQG techniques in terms of the selected criteria. Also it provided more energy saving control strategies and would thereby increase operational duration times for the vehicle during real-time missions.K E Y WO R D S 1. Unmanned Surface Vehicle. 2. Autopilot Design. 3. Linear Quadratic Gaussian Control 4. Local Control Network.

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Navigation and Automatic Control of the Measuring Dolphin (Messin™)

Cited by 19 publications

References 1 publication

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

A review on improving the autonomy of unmanned surface vehicles through intelligent collision avoidance manoeuvres

Non-linear control algorithms for an unmanned surface vehicle

An Autopilot Based on a Local Control Network Design for an Unmanned Surface Vehicle

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