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Optimal hybrid fault recovery in a team of unmanned aerial vehicles

Title:

Optimal hybrid fault recovery in a team of unmanned aerial vehicles

Tousi, M.M. and Khorasani, Khashayar (2012) Optimal hybrid fault recovery in a team of unmanned aerial vehicles. Automatica, 48 (2). pp. 410-418. ISSN 00051098

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Official URL: http://dx.doi.org/10.1016/j.automatica.2011.07.006

Abstract

This paper introduces and develops an optimal hybrid fault recovery methodology for a team of unmanned vehicles by taking advantage of the cooperative nature of the team to accomplish the desired mission requirements in presence of faults/failures. The proposed methodology is developed in a hybrid framework that consists of a low-level (an agent level and a team level) and a high-level (discrete-event system level) fault diagnosis and recovery modules. A high-level fault recovery scheme is proposed within the discrete-event system (DES) supervisory control framework, whereas it is assumed that a low-level fault recovery designed based on classical control techniques is already available. The low-level recovery module employs information on the detected and estimated fault and modifies the controller parameters to recover the team from the faulty condition. By taking advantage of combinatorial optimization techniques, a novel reconfiguration strategy is proposed and developed at the high-level so that the faulty vehicles are recovered with minimum cost to the team. A case study is provided to illustrate and demonstrate the effectiveness of our proposed approach for the icing problem in unmanned aerial vehicles, which is a well-known structural problem in the aircraft industry.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Electrical and Computer Engineering
Item Type:Article
Refereed:Yes
Authors:Tousi, M.M. and Khorasani, Khashayar
Journal or Publication:Automatica
Date:2012
Digital Object Identifier (DOI):10.1016/j.automatica.2011.07.006
ID Code:974138
Deposited By: ANDREA MURRAY
Deposited On:13 Jun 2012 13:38
Last Modified:18 Jan 2018 17:37
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