Safe flying for an UAV helicopter

Mancini, Adriano; Caponetti, Fabio; Monteriù, Andrea; Frontoni, Emanuele; Zingaretti, Primo; Longhi, Sauro

doi:10.1109/med.2007.4433946

Cited by 18 publications

(4 citation statements)

References 12 publications

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“…[1], entre ellas su uso en zonas de alto riesgo o difícil acceso, y la no existencia de un piloto a bordo de la aeronave, por lo que no hay riesgo para su vida facilitando la realización de movimientos con aceleraciones. Entre las desventajas, la aparición de fallos que pueden afectar el desempeño de la misión [2]- [4], la limitación en el tiempo de vuelo por razones energéticas [5] y posibilidad de ser hackeados o neutralizados, siendo vulnerables ante afectaciones de los canales de comunicación [6].…”

Section: Introductionunclassified

Modeling faults of quadcopter aerial vehicle using petri nets

López¹,

Cortés²,

García³

et al. 2019

ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)

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The development of models focused on the detection and diagnosis of failures in autonomous aerial vehicles, constitutes a novel subject, where for this application context the complexity of the algorithms and sensorial systems on board of these vehicles constitutes a challenge. In this field Petri Networks are used as a tool for fault detection given the facilities they provide for the modeling of complex systems in terms of their graphic representation and offering a simple solution. In this investigation a fault model is developed that allows the detection of faults based on Petri Nets applied to an air vehicle type Quadcopter, this model allows to determine the possible existence of off-line faults for this type of aerial vehicle, through the analysis of the data coming from the flight controller and measurements of the sensors on board. It is shown that the model satisfies the properties established for the verification of models with Petri Nets using two of the methods; reachability tree and state equation.

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Section: Introductionunclassified

Modeling faults of quadcopter aerial vehicle using petri nets

López¹,

Cortés²,

García³

et al. 2019

ITEGAM- Journal of Engineering and Technology for Industrial Applications (ITEGAM-JETIA)

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“…2 The level of performance, combined with a relatively low cost, makes devices such as these well-suited for unmanned vehicles applications especially when aided by the global positioning system. [3][4][5] In addition, without aiding, the 3DM-GX1 has previously been demonstrated capable of hovering a micro air vehicle autonomously for 35 seconds and for several minutes when assisting a pilot.…”

Section: Introductionmentioning

confidence: 99%

Field Programmable Gate Array-Based Attitude Stabilization

Stepaniak

Haag

Graas

2009

Journal of Aerospace Computing, Information, and Communication

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A system for determining vehicle attitude using a field programmable gate array (FPGA) and low cost gyroscopes is presented. The method is intended to support the stabilization of a short duration, unmanned aerial vehicle. Using a microelectromechanical system (MEMS) inertial sensor for the calibration and serial interface, the algorithm sidesteps concerns related to electromagnetic interference and the impact of embedded, proprietaryfilters. An Allan variance analysis is used to characterize the sensor errors and predict system performance. A floating point representation using a direction cosine matrix is hosted on the FPGA alongside the platform stabilization feedback loops. Although prone to drifting without additional aiding, the derived attitude has been demonstrated to be effective in stabilizing a remotely piloted quadrotor. Report Documentation PageForm Public reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington Headquarters Services, Directorate for Information Operations and Reports, 1215 Jefferson Davis Highway, Suite 1204, Arlington VA 22202-4302. Respondents should be aware that notwithstanding any other provision of law, no person shall be subject to a penalty for failing to comply with a collection of information if it does not display a currently valid OMB control number.

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“…Further in the literature, we meet systems that use real helicopters for the experiments. In (Dzul, Lozano, and Castillo, 2004) and (Mancini et al, 2007), a mechanical construction holds the helicopter in a stable position allowing only small and safe movements. Using mechanical limitations, the helicopter is able to move in only one or two axes and within limits.…”

Section: Introductionmentioning

confidence: 99%

Altitude Control of Small Helicopters Using a Prototype Test Bed

Vitzilaios

Tsourveloudis

2008

Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics Service

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In this paper we present an experimental test bed for the development and evaluation of control systems for unmanned helicopters. The test bed consists of a small unmanned helicopter, mounted on a flying stand that permits all possible movements but prevents the helicopter from damaging or crashing. A fuzzy controller is developed in MATLAB and tested in the helicopter using the test bed. The controller is able to perform hovering and altitude control. Experimental results are presented for various test cases.

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Safe flying for an UAV helicopter

Cited by 18 publications

References 12 publications

Modeling faults of quadcopter aerial vehicle using petri nets

Modeling faults of quadcopter aerial vehicle using petri nets

Field Programmable Gate Array-Based Attitude Stabilization

Altitude Control of Small Helicopters Using a Prototype Test Bed

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