Neural Controlling of Remotely Operated Underwater Vehicle

Andrzej Żak

doi:10.4028/www.scientific.net/SSP.180.168

Paper Titles

Six-Legged Walking Robot for Inspection Tasks
p.137

Hydroacoustic Multi-Sensor for Positioning Underwater Robots
p.145

Application of the Maggi Equations to Mathematical Modeling of a Robotic Underwater Vehicle as an Object with Superimposed Non-Holonomic Constraints Treated as Control Laws
p.152

Conception of Research on Bionic Underwater Vehicle with Undulating Propulsion
p.160

Neural Controlling of Remotely Operated Underwater Vehicle
p.168

Data Dimension Reduction and Visualization with Application to Multi-Dimensional Gearbox Diagnostics Data: Comparison of Several Methods
p.177

Conception and Practical Application of a Measuring Device for Energetic Parameters Measurement of a Mechatronic Object
p.185

Investigations of the Vibroacoustic Signals Sensitivity to Mechanical Defects Not Recognised by the OBD System in Diesel Engines
p.194

Modelling of the Toothed Gear Operations with the Application of the Analysis of the Gear Sliding Mesh Velocity Changes
p.200

HomeSolid State PhenomenaSolid State Phenomena Vol. 180Neural Controlling of Remotely Operated Underwater...

Neural Controlling of Remotely Operated Underwater Vehicle

Abstract:

The main aim of paper is to introduce the results of research concentrated on controlling remotely operated underwater vehicle using artificial neural networks. Firstly the mathematical basis of neural network using to control dynamical object were introduced. Next the proposed control system which is using technology of artificial neural network was presented. At the end the example results of research on stabilizing movements’ parameters of underwater vehicle using ROV simulator were presented. The paper is finished by summary which include conclusions derive from results of research.

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Periodical:

Solid State Phenomena (Volume 180)

Pages:

168-174

DOI:

https://doi.org/10.4028/www.scientific.net/SSP.180.168

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Online since:

November 2011

Authors:

Andrzej Żak

Keywords:

Artificial Neural Network (ANN), Control System, Dynamic Systems, Underwater Vehicle

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