Design of a Control System for an Organic Flight Array Based on a Neural Network Controller

This paper presents a flight control system for an organic flight array (OFA) with a new configuration consisting of multimodularized ducted-fan unmanned aerial vehicles. The OFA has a distinguished advantage of assembling or separating with respect to its missions or operational conditions because...

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Main Authors: Bokyoung Oh, Junho Jeong, Jinyoung Suk, Seungkeun Kim
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:International Journal of Aerospace Engineering
Online Access:http://dx.doi.org/10.1155/2018/1250908
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spelling doaj-77476092c21040c3b9f8fd5ce2e9fb852020-11-24T21:12:52ZengHindawi LimitedInternational Journal of Aerospace Engineering1687-59661687-59742018-01-01201810.1155/2018/12509081250908Design of a Control System for an Organic Flight Array Based on a Neural Network ControllerBokyoung Oh0Junho Jeong1Jinyoung Suk2Seungkeun Kim3Agency for Defense Development, Daejeon, Republic of KoreaDepartment of Aerospace Engineering, Chungnam National University, Daejeon, Republic of KoreaDepartment of Aerospace Engineering, Chungnam National University, Daejeon, Republic of KoreaDepartment of Aerospace Engineering, Chungnam National University, Daejeon, Republic of KoreaThis paper presents a flight control system for an organic flight array (OFA) with a new configuration consisting of multimodularized ducted-fan unmanned aerial vehicles. The OFA has a distinguished advantage of assembling or separating with respect to its missions or operational conditions because of its reconfigurable structure. Therefore, designing a controller that can be flexibly applied in each situation is necessary. First, a dynamic modeling of the OFA based on a single ducted-fan vehicle is performed. Second, the inner loop for attitude control is designed through dynamic model inversion and a PD controller. However, an adaptive control component is needed to flexibly cope with the uncertainty because the operating environment of the OFA is varied, and uncertainty exists depending on the number of modules to be assembled and disturbances. In addition, the performance of the neural network adaptive controller is verified through a numerical simulation according to two scenarios.http://dx.doi.org/10.1155/2018/1250908
collection DOAJ
language English
format Article
sources DOAJ
author Bokyoung Oh
Junho Jeong
Jinyoung Suk
Seungkeun Kim
spellingShingle Bokyoung Oh
Junho Jeong
Jinyoung Suk
Seungkeun Kim
Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
International Journal of Aerospace Engineering
author_facet Bokyoung Oh
Junho Jeong
Jinyoung Suk
Seungkeun Kim
author_sort Bokyoung Oh
title Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
title_short Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
title_full Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
title_fullStr Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
title_full_unstemmed Design of a Control System for an Organic Flight Array Based on a Neural Network Controller
title_sort design of a control system for an organic flight array based on a neural network controller
publisher Hindawi Limited
series International Journal of Aerospace Engineering
issn 1687-5966
1687-5974
publishDate 2018-01-01
description This paper presents a flight control system for an organic flight array (OFA) with a new configuration consisting of multimodularized ducted-fan unmanned aerial vehicles. The OFA has a distinguished advantage of assembling or separating with respect to its missions or operational conditions because of its reconfigurable structure. Therefore, designing a controller that can be flexibly applied in each situation is necessary. First, a dynamic modeling of the OFA based on a single ducted-fan vehicle is performed. Second, the inner loop for attitude control is designed through dynamic model inversion and a PD controller. However, an adaptive control component is needed to flexibly cope with the uncertainty because the operating environment of the OFA is varied, and uncertainty exists depending on the number of modules to be assembled and disturbances. In addition, the performance of the neural network adaptive controller is verified through a numerical simulation according to two scenarios.
url http://dx.doi.org/10.1155/2018/1250908
work_keys_str_mv AT bokyoungoh designofacontrolsystemforanorganicflightarraybasedonaneuralnetworkcontroller
AT junhojeong designofacontrolsystemforanorganicflightarraybasedonaneuralnetworkcontroller
AT jinyoungsuk designofacontrolsystemforanorganicflightarraybasedonaneuralnetworkcontroller
AT seungkeunkim designofacontrolsystemforanorganicflightarraybasedonaneuralnetworkcontroller
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