Data Analysis of Phoenix RLV Demonstrator Flight Test

Jategaonkar, R.V.; Behr, R.; Gockel, W.; Zorn, Christoph

doi:10.2514/6.2005-6129

Cited by 17 publications

(14 citation statements)

References 2 publications

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“…CARINA was a small system, which was composed of a re-entry module and a service module, [41]. CARINA was a small system, which was composed of a re-entry module and a service module, [41].…”

Section: Carina (Italy)mentioning

confidence: 99%

“…The Italian aerospace company ALENIA SPAZIO was the prime contractor of the CARINA project, [41,42]. For the re-entry module a GEMINI-like shape was chosen, Fig.…”

Section: Configurational Aspectsmentioning

confidence: 99%

“…From the literature it is known that data were generated for 0.8 M ∞ 1.6 and M ∞ = 8, [41,42], but published have been only a few of them. These few data are plotted in .…”

Section: Longitudinal Motionmentioning

confidence: 99%

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Aerodynamic Data of Space Vehicles

Weiland¹

2014

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Section: Carina (Italy)mentioning

confidence: 99%

“…The Italian aerospace company ALENIA SPAZIO was the prime contractor of the CARINA project, [41,42]. For the re-entry module a GEMINI-like shape was chosen, Fig.…”

Section: Configurational Aspectsmentioning

confidence: 99%

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Aerodynamic Data of Space Vehicles

Weiland¹

2014

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“…Furthermore, aerospace companies and research centres have developed programs in the field of autonomy in UAVs, also covering the automatic landing issue [5][6][7] .…”

Section: Introductionmentioning

confidence: 99%

Adaptive Algorithm for Fixed Wing UAV Autolanding on Aircraft Carrier

Lellis

Vito

Ruby

et al. 2013

AIAA Infotech@Aerospace (I@A) Conference

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Ruby M., Salbego N. French Air Force AcademyThis paper presents an adaptive algorithm for autolanding of a fixed wing UAV on an aircraft carrier. The algorithm is characterized by the specific feature of implementing suitable adaptivity in order to improve the ability of a UAV in performing the automatic landing on a moving runway, such as an aircraft carrier. Furthermore, in order to consider the specific requirements and constraints associated to the autonomous approach and landing of a UAV on an aircraft carrier, the algorithm properly takes into account the procedures typically used by Navy's pilot to land on the aircraft carrier. The paper is structured into several paragraphs describing both the proposed algorithm and its numerical validation results. More in details, in the paper first a summary state-of-the-art of autolanding algorithms is outlined, then the overall Guidance, Navigation and Control system architecture, where the autolanding algorithm is integrated, is introduced and the proposed algorithm is described. The design philosophy is illustrated, which is based on the consideration of the autolanding trajectory generation problem according to two stages: the plan of a nominal trajectory applicable to the ideal case and the periodical regeneration, real time during the mission, of a new trajectory, according to the current state of both vehicle and carrier. In the second part of the paper, finally, the synthetic environment used for the numerical validation of the proposed algorithm is described and the results of the validation campaign are reported and commented, showing the effectiveness of the proposed algorithm even in presence of external disturbances.

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“…Different approaches have been proposed to address the aircrafts automatic landing, based on the use of both modern intelligent control techniques and classical control theory [3][4][5][6][7] , and aerospace companies and research centres have developed programs in the field of autonomy in UAVs, also covering the automatic landing issue [6][7][8] .…”

Section: Introductionmentioning

confidence: 99%

Flight Testing of a Fully Adaptive Algorithm for Autonomous Fixed Wing Aircrafts Landing

Lellis

Vito

Marrone

et al. 2012

Infotech@Aerospace 2012

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This paper presents the flight test results of a fully adaptive algorithm for autonomous fixed wing aircrafts landing developed by CIRA, the Italian Aerospace Research Centre. The algorithm is designed and implemented in the framework of a complete autonomous guidance system, worked out by CIRA, able to allow autonomous way-points navigation, autonomous landing and autonomous collision avoidance for fixed wing aircrafts. The algorithm presented in the paper is designed to perform a fully adaptive autonomous landing starting from any point of the three dimensional space, based on the use of the DGPS/AHRS technology. Main features of the autolanding system based on the implementation of the proposed algorithm are: on line landing trajectory re-planning, fully autonomy from pilot inputs, weakly instrumented landing runway, ability to land starting from any point in the space and autonomous management of failures and/or adverse atmospheric conditions. The flight tests have been conducted at an airfield in Caserta, in the south of Italy, close the CIRA. The paper is structured into several paragraphs describing the algorithm designed for the autolanding maneuver, the control system architecture and the methodologies developed in order to safely manage the possible presence of failures and/or unfavorable weather conditions, the preliminary results of the real time validation with hardware in the loop simulation and, finally, the performances achieved by using the CIRA experimental flying platform, with reference to the real flight experiments. Nomenclature X = position along X-Runway axis ) ( X V X = inertial velocity profile along X-Runway axis ) ( X V Z = inertial velocity profile along Z-Runway axis ) ( X H = position profile along Z-Runway axis 0 H = initial position along Z-Runway axis 0 X = initial position along X-Runway axis 0 X V = initial inertial velocity profile along X-Runway axis F H = desired final position along Z-Runway axis F X = desired final position along X-Runway axis XF V = desired final inertial velocity profile along X-Runway axis ZF V = desired final inertial velocity profile along Z-Runway axis

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Data Analysis of Phoenix RLV Demonstrator Flight Test

Cited by 17 publications

References 2 publications

Aerodynamic Data of Space Vehicles

Aerodynamic Data of Space Vehicles

Adaptive Algorithm for Fixed Wing UAV Autolanding on Aircraft Carrier

Flight Testing of a Fully Adaptive Algorithm for Autonomous Fixed Wing Aircrafts Landing

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