A Low Cost Small UAV Flight Research Facility

Murch, Austin; Paw, Yew Chai; Pandita, Rohit; Li, Zhefeng; Balas, Gary J.

doi:10.1007/978-3-642-19817-5_3

Cited by 24 publications

(13 citation statements)

References 3 publications

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“…Physical properties of the airframe are summarized in Table 1, where the moments of inertia are calculated using swing tests. More details on the University of Minnesota Ultra Stick 25e platform can be found in [12,16].…”

Section: A Airframe and Instrumentationmentioning

confidence: 99%

“…The second identification step fits the linear state-space models [described by Eqs. (16) and (17)] to the extracted frequency responses. Parameters in the linear models are identified through a nonlinear optimization that minimizes the fitting error in the frequency domain.…”

Section: Frequency Domain System Identificationmentioning

confidence: 99%

“…(16)] to the estimated frequency responses given fixed actuator dynamics and system time delay. The results are used to update the baseline model, which completes the longitudinal axis identification process.…”

Section: A Longitudinal Dynamicsmentioning

confidence: 99%

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System Identification for Small, Low-Cost, Fixed-Wing Unmanned Aircraft

Dorobantu

Murch

Mettler

et al. 2013

Journal of Aircraft

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This paper describes a practical system identification procedure for small, low-cost, fixed-wing unmanned aircraft. Physical size and cost restrictions limit the sensing capabilities of these vehicles. The procedure is demonstrated on an Ultra Stick 25e, therefore emphasizing a minimum complexity approach compatible with a low-cost inertial sensor. A linear model, obtained from the generic nonlinear equations of motion for aircraft, is used as a basis for system identification. This model is populated with results from a first principles analysis to form a baseline model. Flight experiments are designed using the baseline model and operational constraints to collect informative data. Parameters of the linear model are identified by fitting the model to frequency responses extracted from the data. The parameters are integrated into the nonlinear equations of motion, and both linear and nonlinear models are validated in the time domain. Verification of model accuracy is extended with a sensitivity and residual analysis.

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Section: A Airframe and Instrumentationmentioning

confidence: 99%

Section: Frequency Domain System Identificationmentioning

confidence: 99%

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System Identification for Small, Low-Cost, Fixed-Wing Unmanned Aircraft

Dorobantu

Murch

Mettler

et al. 2013

Journal of Aircraft

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“…Developing a UAV research platform to validate these new principles and technologies is of great importance, and so it is no surprise that many UAV testbeds have been developed by various academic groups, e.g., [9,20,25,26,32,36,38,40,42]. The main goal in building our testbed is to develop a lowcost and reliable fixed-wing UAV platform that can be used to implement relatively complex control algorithms.…”

Section: Introductionmentioning

confidence: 99%

“…Building a low-cost UAV platform is not an original idea, as other research groups in the control and robotics community have done so. For instance, the UAV research group at the University of Minnesota have developed a low-cost UAV testbed [11,38], which is mostly built of commercial-off-the-shelf (COTS) components and uses the radio-controlled (R/C) fixed-wing UAV, Ultra Stick 25e, as the main test aircraft. Another low-cost UAV platform, based on the R/C Goldberg Decathlon ARF airframe, has been developed at Georgia Tech [26] for educational purposes.…”

Section: Introductionmentioning

confidence: 99%

Development and Modeling of a Low-Cost Unmanned Aerial Vehicle Research Platform

Arifianto

Farhood

2014

J Intell Robot Syst

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This paper describes the development and modeling of a low-cost and reliable small unmanned aerial vehicle research platform for advanced control implementation. The platform is mostly constructed of low-cost commercial-off-the-shelf (COTS) components. The only non-COTS components are the airdata probes, which are manufactured and calibrated in-house. The airframe used is the commercially available radio-controlled (R/C) 6-foot Telemaster airplane from Hobby Express, chosen mainly for its adequately spacious fuselage and for being reasonably stable and sufficiently agile. One noteworthy feature of this platform is the use of two separate low-cost onboard computers for handling the data management/hardware interfacing and control computation. Specifically, the single board computer, Gumstix Overo Fire, is used to execute the control algorithms, whereas the open source autopilot, Ardupilot Mega, is mostly used to interface the Overo computer with the sensors and actuators. The platform supports multi-vehicle operations through the use of a radio modem that enables multi-point communications. As the goal of this platform is to implement rigorous control algorithms for real-time trajectory tracking and distributed control, it O. Arifianto · M. Farhood ( ) is important to derive an appropriate flight dynamic model of the platform, based on which the controllers will be synthesized. For that matter, the paper provides reasonably accurate models of the vehicle, servomotors, and propulsion system. Namely, the output error method is used to estimate the longitudinal and lateraldirectional aerodynamic parameters from flight test data. The moments of inertia of the platform are determined using the simple pendulum test method, and the frequency response of each servomotor is also obtained experimentally. The Javaprop applet is used to obtain lookup tables relating airspeed to propeller thrust at constant throttle settings.

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