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Intelligent supervisory switching co...

Bertaska, Ivan Rodrigues.

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Intelligent supervisory switching control of unmanned surface vehicles.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Intelligent supervisory switching control of unmanned surface vehicles./
Author:	Bertaska, Ivan Rodrigues.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2016,
Description:	283 p.
Notes:	Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
Contained By:	Dissertation Abstracts International78-05B(E).
Subject:	Ocean engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10300337
ISBN:	9781369423761

Intelligent supervisory switching control of unmanned surface vehicles.
Bertaska, Ivan Rodrigues.

Intelligent supervisory switching control of unmanned surface vehicles. - Ann Arbor : ProQuest Dissertations & Theses, 2016 - 283 p.

Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.

Thesis (Ph.D.)--Florida Atlantic University, 2016.

A novel approach to extend the decision-making capabilities of unmanned surface vehicles (USVs) is presented in this work. A multi-objective framework is described where separate controllers command different behaviors according to a desired trajectory. Three behaviors are examined -- transiting, station-keeping and reversing. Given the desired trajectory, the vehicle is able to autonomously recognize which behavior best suits a portion of the trajectory. The USV uses a combination of a supervisory switching control structure and a reinforcement learning algorithm to create a hybrid deliberative and reactive approach to switch between controllers and actions. Reinforcement learning provides a deliberative method to create a controller switching policy, while supervisory switching control acts reactively to instantaneous changes in the environment. Each action is restricted to one controller. Due to the nonlinear effects in these behaviors, two underactuated backstepping controllers and a fully-actuated backstepping controller are proposed for each transiting, reversing and station-keeping behavior, respectively, restricted to three degrees of freedom. Field experiments are presented to validate this system on the water with a physical USV platform under Sea State 1 conditions. Main outcomes of this work are that the proposed system provides better performance than a comparable gain-scheduled nonlinear controller in terms of an Integral of Absolute Error metric. Additionally, the deliberative component allows the system to identify dynamically infeasible trajectories and properly accommodate them.

ISBN: 9781369423761Subjects--Topical Terms:

660731
Ocean engineering.

Intelligent supervisory switching control of unmanned surface vehicles.
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100 1 $a Bertaska, Ivan Rodrigues. $3 3278873
245 1 0 $a Intelligent supervisory switching control of unmanned surface vehicles.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2016
300 $a 283 p.
500 $a Source: Dissertation Abstracts International, Volume: 78-05(E), Section: B.
500 $a Adviser: Karl von Ellenrieder.
502 $a Thesis (Ph.D.)--Florida Atlantic University, 2016.
520 $a A novel approach to extend the decision-making capabilities of unmanned surface vehicles (USVs) is presented in this work. A multi-objective framework is described where separate controllers command different behaviors according to a desired trajectory. Three behaviors are examined -- transiting, station-keeping and reversing. Given the desired trajectory, the vehicle is able to autonomously recognize which behavior best suits a portion of the trajectory. The USV uses a combination of a supervisory switching control structure and a reinforcement learning algorithm to create a hybrid deliberative and reactive approach to switch between controllers and actions. Reinforcement learning provides a deliberative method to create a controller switching policy, while supervisory switching control acts reactively to instantaneous changes in the environment. Each action is restricted to one controller. Due to the nonlinear effects in these behaviors, two underactuated backstepping controllers and a fully-actuated backstepping controller are proposed for each transiting, reversing and station-keeping behavior, respectively, restricted to three degrees of freedom. Field experiments are presented to validate this system on the water with a physical USV platform under Sea State 1 conditions. Main outcomes of this work are that the proposed system provides better performance than a comparable gain-scheduled nonlinear controller in terms of an Integral of Absolute Error metric. Additionally, the deliberative component allows the system to identify dynamically infeasible trajectories and properly accommodate them.
590 $a School code: 0119.
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650 4 $a Robotics. $3 519753
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710 2 $a Florida Atlantic University. $3 1017837
773 0 $t Dissertation Abstracts International $g 78-05B(E).
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856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10300337