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Dynamic Modeling and System Identification of a Surface Marine Vehicle for Autonomous Swarm Applications

[+] Author Affiliations
Nikolaos I. Xiros

University of New Orleans, New Orleans, LA

Eleftherios K. Loghis

National Technical University of Athens, Athens, Greece

Paper No. IMECE2012-89404, pp. 807-816; 10 pages
  • ASME 2012 International Mechanical Engineering Congress and Exposition
  • Volume 4: Dynamics, Control and Uncertainty, Parts A and B
  • Houston, Texas, USA, November 9–15, 2012
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4520-2
  • Copyright © 2012 by ASME


The scale model of a surface marine vehicle with electric propulsion by a dc motor and waterjet is built. The intention is to serve as prototype for dynamic modeling and system identification of a class of vehicles for autonomous swarm applications. A first step towards this end is to develop a mathematical model capable to adequately describe the motion of the vehicle under a variety of conditions. Such model is developed by fusing basic principles with data series obtained through a series of test basin experiments. The aim is to minimize the number and cost of sensors needed in this end, without unacceptably compromising accuracy, by employing knowledge of vehicle dynamics in order to form a customized gray-box modeling approach. A set of nonlinear differential equations, used to depict the behavior of the marine vehicle at hand are derived. This dynamic model will form the basis for applying physicomimetic approaches to control and navigation of a standalone or swarm of similar vehicles. In the physicomimetic controller synthesis approach, the control problem is tackled by the concept of virtual forces acting on the vehicle and in result generating motion patterns that are favored for a certain application, e.g. avoid obstacles and collisions. By the term virtual forces we refer to forces not actually existing but rather introduced to the system of interest through means of local-loop vehicle control. To achieve physicomimetic control one needs to effectively cancel the actual dynamics or physics to which a vehicle’s motion complies with and then impose the desired dynamics as virtual forces. In the present work, a series of open loop experiments will allow us to develop the actual dynamics of vehicle motion. At the same time, sensors will also provide active feedback required by the controllers to adjust the vehicle’s dynamic response and behavior so that it can be made compliant with an arbitrary virtual force at a later stage.

Copyright © 2012 by ASME



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