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A robust adaptive neural network con...

Nicol, Christopher Edmond.

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A robust adaptive neural network control for a quadrotor helicopter.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	A robust adaptive neural network control for a quadrotor helicopter./
Author:	Nicol, Christopher Edmond.
Description:	182 p.
Notes:	Source: Masters Abstracts International, Volume: 48-06, page: 3805.
Contained By:	Masters Abstracts International48-06.
Subject:	Engineering, Aerospace. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR62088
ISBN:	9780494620885

A robust adaptive neural network control for a quadrotor helicopter.
Nicol, Christopher Edmond.

A robust adaptive neural network control for a quadrotor helicopter. - 182 p.

Source: Masters Abstracts International, Volume: 48-06, page: 3805.

Thesis (M.Sc.)--University of Calgary (Canada), 2010.

A quadrotor helicopter is a highly nonlinear and open-loop unstable system, presenting significant challenges in terms of control design. This thesis proposes a neural network based controller, which makes use of a new robust technique to avoid weight drift caused by persistent disturbances, and describes the development of a working prototype for testing purposes. The controller consists of an adaptive neural network for attitude/altitude control and adaptation, and a position control to design roll and pitch angles/velocities. When the new robust technique is applied in simulation, results demonstrate the control design is able to stabilize the quadrotor, while avoiding weight drift. After implementing the adaptive neural network on the prototype, experiments demonstrate that the control is able to stabilize the quadrotor, that nonlinear techniques provide a wider operating range than linear controls, and that weight drift is as much of a problem practically, as it is theoretically.

ISBN: 9780494620885Subjects--Topical Terms:

1018395
Engineering, Aerospace.

A robust adaptive neural network control for a quadrotor helicopter.
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020 $a 9780494620885
035 $a (UMI)AAIMR62088
035 $a AAIMR62088
040 $a UMI $c UMI
100 1 $a Nicol, Christopher Edmond. $3 1682887
245 1 2 $a A robust adaptive neural network control for a quadrotor helicopter.
300 $a 182 p.
500 $a Source: Masters Abstracts International, Volume: 48-06, page: 3805.
502 $a Thesis (M.Sc.)--University of Calgary (Canada), 2010.
520 $a A quadrotor helicopter is a highly nonlinear and open-loop unstable system, presenting significant challenges in terms of control design. This thesis proposes a neural network based controller, which makes use of a new robust technique to avoid weight drift caused by persistent disturbances, and describes the development of a working prototype for testing purposes. The controller consists of an adaptive neural network for attitude/altitude control and adaptation, and a position control to design roll and pitch angles/velocities. When the new robust technique is applied in simulation, results demonstrate the control design is able to stabilize the quadrotor, while avoiding weight drift. After implementing the adaptive neural network on the prototype, experiments demonstrate that the control is able to stabilize the quadrotor, that nonlinear techniques provide a wider operating range than linear controls, and that weight drift is as much of a problem practically, as it is theoretically.
590 $a School code: 0026.
650 4 $a Engineering, Aerospace. $3 1018395
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, Robotics. $3 1018454
650 4 $a Artificial Intelligence. $3 769149
690 $a 0538
690 $a 0544
690 $a 0771
690 $a 0800
710 2 $a University of Calgary (Canada). $3 1017619
773 0 $t Masters Abstracts International $g 48-06.
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791 $a M.Sc.
792 $a 2010
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=MR62088