Model identification of a Micro Air Vehicle

Niño, Jorge; Mitrache, Flavius; Cosyn, Peter; Keyser, Robin De

doi:10.1016/s1672-6529(07)60036-5

Cited by 29 publications

(7 citation statements)

References 4 publications

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“…According to the forms of the typical first order systems considered and the FOPI controller discussed, we can systemically design the FOPI controller following the three specifications introduced in Sec. 2.…”

Section: Fopi Controller Design For the Typical First Order Systemsmentioning

confidence: 99%

“…A lot of researchers have looked into the problem of UAV modeling and control. Open loop steady state flight experiments are proposed for the aileron-(roll rate) and elevator-(pitch rate) loop system identification respectively [2]. But the open loop system identification requires special requirements on UAV flight stability, which limit the roll and pitch reference signals to be as small as 0.02 rad.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Fractional Order Flight Control of a Small Fixed-Wing UAV: Controller Design and Simulation Study

Huo

Luo

et al. 2009

Volume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stres

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This paper focuses on designing and implementation of fractional order proportional integral (PIα) flight controller on a small fixed-wing unmanned aerial vehicle (UAV). It describes mainly the controller design and simulation studies. The basics of UAV flight control are introduced first with a special emphasis on small UAV platforms. Time domain system identification methods are tried on the UAV roll channel. A new fractional order PI controller design method is then provided based on the identified first order model. The fractional order PIα controller can outperform the traditional integer order PID controller because it has a larger memory and more candidate solutions to choose. The simulation results show the effectiveness of the proposed controller design strategy and the robustness of fractional order controller under conditions of wind gusts and various pay-loads.

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Section: Fopi Controller Design For the Typical First Order Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fractional Order Flight Control of a Small Fixed-Wing UAV: Controller Design and Simulation Study

Huo

Luo

et al. 2009

Volume 3: ASME/IEEE 2009 International Conference on Mechatronic and Embedded Systems and Applications; 20th Reliability, Stres

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“…4 Several other work investigated the identification techniques for small or larger UAVs. [5][6][7] In most cases, the goal is to produce a state space model directly usable for applying advanced control theory, hence focusing on the dynamics. The work from Edwards 8 proposes a simple and practical method to extract lift and drag coefficients from flight tests based on analysis on gliding phases.…”

Section: Introductionmentioning

confidence: 99%

In-Flight Thrust Measurement using On-Board Force Sensor

Bronz

Marina

Hattenberger

2017

AIAA Atmospheric Flight Mechanics Conference

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Preliminary results of an in-flight thrust measurement method are presented in order to determine the drag force. Flight experiments are conducted by an off-the-shelf aircraft which has been equipped with an autopilot system and additional sensors measuring the electric motor rotation speed, battery voltage, drawn current, and direct thrust of the motor. Several level cruise flights have been performed in order to measure the thrust, thus the drag force generated by the aircraft. The propulsion system used on the aircraft is first characterized in the wind-tunnel. The direct thrust measurement system which is on-board the aircraft presents a lot of noise coming from vibrations, characteristics of the sensor itself, and also the fuselage wake and propeller interaction. Hence a better estimation of the in-flight thrust and the resultant drag is obtained by sensor fusion of Gaussian signals.

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“…Several work are presenting identification techniques for small or larger UAVs. [2][3][4] In most cases, the goal is to produce a state space model directly usable for applying advanced control theory, hence focusing on the dynamics. The work from Edwards 5 proposes a simple and practical methods to extract lift and drag coefficients from flight tests based on gliding phases analysis.…”

Section: Introductionmentioning

confidence: 99%

Aerodynamic Characterization of an Off-the-Shelf Aircraft via Flight Test and Numerical Simulation

Bronz

Hattenberger

2016

AIAA Flight Testing Conference

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International audienceCharacterization of an off-the-shelf small tailless aircraft with a wing span of 1:3m is presented. Mentioned aircraft is being used in several scientific measurement projects by authors, whereas the ight performance and quality such as endurance, and stability plays an important role on the measurement quality. Hence the main objective is to use the extracted and fine tuned aerodynamic and ight performance characteristics of the aircraft for a better flight control and mission planning during simulations and real flights. Aerodynamic characteristics are obtained through flighttests, numerical analyses, and some isolated ground experiments for the propulsion system. The comparison of different measurement and estimation techniques are discussed

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Model identification of a Micro Air Vehicle

Cited by 29 publications

References 4 publications

Fractional Order Flight Control of a Small Fixed-Wing UAV: Controller Design and Simulation Study

Fractional Order Flight Control of a Small Fixed-Wing UAV: Controller Design and Simulation Study

In-Flight Thrust Measurement using On-Board Force Sensor

Aerodynamic Characterization of an Off-the-Shelf Aircraft via Flight Test and Numerical Simulation

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