Fuzzy Logic Control System for Autonomous Sailboats

Stelzer, Roland; Pröll, Tobias; John, Robert

doi:10.1109/fuzzy.2007.4295347

Cited by 65 publications

(27 citation statements)

References 6 publications

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“…So, a fuzzy logic controller (FLC) capable of simulating human expert behavior seems to be a proper choice. FLCs are widely used for that purpose in the literature [3,4]. One can model the controller by simply writing down the linguistic rules that also direct a human operator.…”

Section: Introductionmentioning

confidence: 99%

Implementation of Fuzzy Control for Surface Platforms in a Computer Generated Forces Toolkit

Senyurek

Koksal

Genç

et al. 2008

2008 International Conference on Computational Intelligence for Modelling Control &Amp; Automation

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Realistic models and realistic control is vital to reach a sufficient fidelity in military simulation projects including surface platforms. In this study, a fuzzy logic controller (FLC) is implemented in conjunction with environment models and platform motion models possessing high-fidelity. The former one considers waves, current, wind, season, day and night while the latter trusts on complex motion equations, including the effect of hydrodynamic force-moments and their high performance is proved by comparison with real cruise data. The FLC is optimized with a recently introduced method, namely Big Bang-Big Crunch algorithm. After all, the controllers are integrated to the component architecture of VR-Forces, which is a commercial framework for developing Computer Generated Forces (CGF) applications.

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Section: Introductionmentioning

confidence: 99%

Implementation of Fuzzy Control for Surface Platforms in a Computer Generated Forces Toolkit

Senyurek

Koksal

Genç

et al. 2008

2008 International Conference on Computational Intelligence for Modelling Control &Amp; Automation

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“…Current electronic autopilots rely on various input data to steer a sailing boat, including the heading, course, wind and heeling angle. Computerized control systems allow the application of sophisticated methods like fuzzy-sets [2], [3], neural networks [4] or other artificial intelligence techniques [5] as a means to handle the steering control much like a human does.…”

Section: Introductionmentioning

confidence: 99%

FASt - an autonomous sailing platform for oceanographic missions

Alves

Cruz

2008

Oceans 2008

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Abstract-Sailing has been for long times the only means of ship propulsion at sea. Although the performance of a sailing vessel is well below the present power driven ships, either in terms of navigation speed and predictability, wind energy is absolutely renewable, clean and free. Unmanned autonomous sailing boats may exhibit a virtually unlimited autonomy and be able to perform unassisted missions at sea for long periods of time. Promising applications include oceanographic and weather data collecting, surveillance and even military applications. The Microtransat competition, launched in Europe in 2006, has been a key initiative to promote the development of robotic unmanned sailing boats. Various regattas have taken place across Europe and the ultimate challenge will be a transatlantic race. This paper presents an autonomous sailing boat developed at the University of Porto, Portugal, with emphasis on the hardware and software computing infrastructure. This platform is capable of carrying a few kilograms of sensing equipment that can be hooked to the boat's main computer, also providing support for short and long range data communications.

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“…As proven in many field tests, autonomous boat navigation systems cannot easily replace human operators due to uncontrollable factors such as wind and waves [16,17]. On the other hand, knowledge of sailing experts can be transformed into a fuzzy interference system in order to steer sails and rudder according to weather conditions and target [16].…”

Section: Related Workmentioning

confidence: 99%

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

Michailidis

Tuna

Gezer

et al. 2014

International Journal of Distributed Sensor Networks

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Underwater sensor networks (USNs) can be used for several types of commercial and noncommercial applications. However, some constraints resulting from the nature of aquatic environments severely limit their use. Due to constraints such as large propagation latency, low-bandwidth capacity, and short-distance communications, a large number of USN nodes are deployed to provide reliability in most applications. In this study, an unattended deployment approach based on the use of an autonomous boat group is proposed. A map of the deployment zone and optimal locations of USN nodes are fed into the onboard computers of the boat group. After processing these data and determining paths to be followed, the boat group deploys sensor nodes at predetermined locations. During the deployment, the boat group is controlled by an artificial neural network-(ANN-) based control system for reducing path errors. A set of performance evaluations is given to prove efficiency of the proposed control system. Performance results show that the boat group can successfully follow a predefined path set and deploy USN nodes. The tradeoffs between energy consumptions, end-to-end delay, and number of hops between underwater relay nodes of energy-efficient USN are also examined. The results indicate that increasing the number of hops reduces the total energy consumption and the end-to-end delay.

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Fuzzy Logic Control System for Autonomous Sailboats

Cited by 65 publications

References 6 publications

Implementation of Fuzzy Control for Surface Platforms in a Computer Generated Forces Toolkit

Implementation of Fuzzy Control for Surface Platforms in a Computer Generated Forces Toolkit

FASt - an autonomous sailing platform for oceanographic missions

ANN-Based Control of a Multiboat Group for the Deployment of an Underwater Sensor Network

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