Avionics Design for a Sub-Scale Fault- Tolerant Flight Control Test-Bed

Gu, Yu; Gross, Jason N.; Barchesky, Francis; Huo, Chao; Napolitano, Marcello R.

doi:10.5772/38260

Cited by 23 publications

(25 citation statements)

References 17 publications

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“…The propulsion system is comprised of two brushless electric ducted fans that are positioned on the fuselage behind the wings. The follower's onboard 5 th generation avionics [32], Gen-V system, features a custom flight computer, nose sensor suite, IMU, control signal distribution board, R/C sub-system, communication sub-system, power sub-system, and real-time software. An onboard GO-PRO® camera records point of view video.…”

Section: B Test Bed Aircraft and Avionicsmentioning

confidence: 99%

Control performance analysis for autonomous close formation flight experiments

Rice

Huo

et al. 2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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Close Formation Flight is a key potential approach for reducing greenhouse gas emissions and managing traffic in future high density airspace. This paper discusses the implementation and flight testing of a formation flight controller. Experimental results show that an autonomous close formation flight with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned research aircraft.

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Section: B Test Bed Aircraft and Avionicsmentioning

confidence: 99%

Control performance analysis for autonomous close formation flight experiments

Rice

Huo

et al. 2014

2014 International Conference on Unmanned Aircraft Systems (ICUAS)

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“…The Gen-V flight computer performs data acquisition, signal conditioning, and signal distribution as well as flight control and failure accommodation functions [44]. It is capable of integrating and distributing control command from five different sources: ground R/C safety pilot, ground research pilot, aircraft on-board flight control system, onboard failure emulation system, and On-Board Excitation System (OBES).…”

Section: Phastball: Fixed Wing Test Bedmentioning

confidence: 99%

“…Two brushless electric ducted fans are mounted to a carbon fiber tube on the fuselage just behind the wings. The follower aircraft's onboard 5th generation avionics [44], Gen-V system, features a custom flight computer, nose sensor suite, IMU, control signal distribution board, R/C subsystem, communication subsystem, power subsystem, and real-time software. An onboard GoPro5 camera records inflight video from off the nose.…”

Section: Phastball: Fixed Wing Test Bedmentioning

confidence: 99%

Autonomous Close Formation Flight Control with Fixed Wing and Quadrotor Test Beds

Rice

Huo

et al. 2016

International Journal of Aerospace Engineering

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Autonomous formation flight is a key approach for reducing energy cost and managing traffic in future high density airspace. The use of Unmanned Aerial Vehicles (UAVs) has allowed low-budget and low-risk validation of autonomous formation flight concepts. This paper discusses the implementation and flight testing of nonlinear dynamic inversion (NLDI) controllers for close formation flight (CFF) using two distinct UAV platforms: a set of fixed wing aircraft named "Phastball" and a set of quadrotors named "NEO." Experimental results show that autonomous CFF with approximately 5-wingspan separation is achievable with a pair of low-cost unmanned Phastball research aircraft. Simulations of the quadrotor flight also validate the design of the NLDI controller for the NEO quadrotors.

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“…It can perform functions including data acquisition, signal conditioning and distribution, global positioning system/inertial navigation system (GPS/INS) sensor fusion, Guidance Navigation and Control (GNC), failure emulation, and aircraft health monitoring. Processes such as attitude estimation, data logging, and actuator command generation takes place at 50 Hz in the Gen-V avionics [22]. During "Phastball" flight the pilot can choose to operate in the Pilot-In-Loop (PIL) or Non-PIL modes.…”

Section: Flight Experimentsmentioning

confidence: 99%

Analysis of Pilot-Induced-Oscillation and Pilot Vehicle System Stability Using UAS Flight Experiments

Mandal

2016

Aerospace

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This paper reports the results of a Pilot-Induced Oscillation (PIO) and human pilot control characterization study performed using flight data collected with a Remotely Controlled (R/C) unmanned research aircraft. The study was carried out on the longitudinal axis of the aircraft. Several existing Category 1 and Category 2 PIO criteria developed for manned aircraft are first surveyed and their effectiveness for predicting the PIO susceptibility for the R/C unmanned aircraft is evaluated using several flight experiments. It was found that the Bandwidth/Pitch rate overshoot and open loop onset point (OLOP) criteria prediction results matched flight test observations. However, other criteria failed to provide accurate prediction results. To further characterize the human pilot control behavior during these experiments, a quasi-linear pilot model is used. The parameters of the pilot model estimated using data obtained from flight tests are then used to obtain information about the stability of the Pilot Vehicle System (PVS) for Category 1 PIOs occurred during straight and level flights. The batch estimation technique used to estimate the parameters of the quasi-linear pilot model failed to completely capture the compatibility nature of the human pilot. The estimation results however provided valuable insights into the frequency characteristics of the human pilot commands. Additionally, stability analysis of the Category 2 PIOs for elevator actuator rate limiting is carried out using simulations and the results are compared with actual flight results.

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Avionics Design for a Sub-Scale Fault- Tolerant Flight Control Test-Bed

Cited by 23 publications

References 17 publications

Control performance analysis for autonomous close formation flight experiments

Control performance analysis for autonomous close formation flight experiments

Autonomous Close Formation Flight Control with Fixed Wing and Quadrotor Test Beds

Analysis of Pilot-Induced-Oscillation and Pilot Vehicle System Stability Using UAS Flight Experiments

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