Rigid-Body Kinematics Versus Flapping Kinematics of a Flapping Wing Micro Air Vehicle

Caetano, J. V.; Weehuizen, M.B.; Visser, Coen C. de; Croon, Guido de; Mulder, Max

doi:10.2514/1.g000923

Cited by 12 publications

(9 citation statements)

References 25 publications

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“…eqs. [8][9][10][11][12][13][14][15][16][17][18][19] were found to converge in the static case, while during flight they vary to a limited extent, typically in conjunction with maneuvers. It can for instance be observed in fig.…”

Section: A Fusion Resultsmentioning

confidence: 99%

“…Nonetheless, comparing forces estimated from the IMU alone to wind tunnel data [35] showed an overall adequate agreement, with minor discrepancies. While no true values are available for validation, and there are known to be some differences between wind tunnel and free-flight forces [13], this observation nonetheless suggests that at sub-flap cycle level, the IMU information can be considered sufficiently reliable.…”

Section: Otmentioning

confidence: 98%

“…While significant insight is now available on both fronts, thanks to studies on insects and birds [1,2,3,4], and, more recently, increasingly on robotic test platforms [5,6,7,8,9,10,11,12,13,14,15], the high complexity of flapping flight still poses a considerable challenge to FWMAV development. Additionally, it is still considerably difficult to obtain realistic experimental data, particularly in free flight and in different flight regimes.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Onboard/Offboard Sensor Fusion for High-Fidelity Flapping-Wing Robot Flight Data

Armanini

Karásek

Croon

et al. 2017

Journal of Guidance, Control, and Dynamics

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Section: A Fusion Resultsmentioning

confidence: 99%

Section: Otmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Onboard/Offboard Sensor Fusion for High-Fidelity Flapping-Wing Robot Flight Data

Armanini

Karásek

Croon

et al. 2017

Journal of Guidance, Control, and Dynamics

Self Cite

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“…Although the DelFly Nimble does not resemble an conventional aircraft, previous studies have shown that these EOM can describe the motion of some flapping-wing flyers [28,29,30,31]. In addition, we do not know the dynamics of the DelFly Nimble very well yet therefore, the use of standard aircraft EOM is a logical first step.…”

Section: Longitudinal Grey-box Model Identification Of the Delfly Nimmentioning

confidence: 98%

Longitudinal Grey-Box Model Identification of a Tailless Flapping-Wing MAV Based on Free-Flight Data

Nijboer

Armanini

Karásek

et al. 2020

AIAA Scitech 2020 Forum

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List of Symbols Actuator output of closed-loop automatic feedback system Control deflection. Measured dihedral deflection [deg] Reference signal of closed-loop automatic feedback system Error signal of closed-loop automatic feedback system Controller output signal of closed-loop automatic feedback system Output system Measured output system , , Position [m] , , , Attitude quaternions Roll rate Pitch rate Yaw ratė Roll acceleratioṅ Pitch acceleratioṅ Yaw acceleration Linear acceleration in x-direction Linear acceleration in y-direction Linear acceleration in z-direction Pitch attitude angle set-point Flapping frequency [Hz] Pitch angle referencė Pitch rate reference Measured pitch anglė Measured pitch rate Rate feedback gain Attitude feedback gaiṅ Derivative of x at time t Measured aerodynamic force in x-direction [N] Measured aerodynamic force in y-direction [N] Measured aerodynamic force in z-direction [N] Measured aerodynamic moment around the x-axis [Nm] Measured aerodynamic moment around the y-axis [Nm] Measured aerodynamic moment around the z-axis [Nm] Mass [kg] Gravitational acceleration [m/s2] Velocity along the body x-axis [m/s] Velocity along the body y-axis [m/s] Velocity along the body z-axis [m/s] Acceleration along the body x-axis [m/s2] Acceleration along the body y-axis [m/s2] Acceleration along the body z-axis [m/s2] Pitch angle Trimmed pitch angle Roll angle Yaw angle Angle of attack Moments of inertia of a

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“…The figure presents the forces determined from both experimental methods. The plot on the left shows the evolution of the forces acting on the FWMAV in free flight computed using single rigid body kinematics [68] -the forces from rigid body kinematics are shown for a better fit with the wind tunnel forces, since both capture inertial and aerodynamic effects. The plot on the right shows the forces obtained from the force transducer in the wind tunnel.…”

Section: Coefficient Valuementioning

confidence: 99%

Quasi-steady aerodynamic model of clap-and-fling flapping MAV and validation using free-flight data

et al. 2016

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Flapping-wing aerodynamic models that are accurate, computationally efficient and physically meaningful, are challenging to obtain. Such models are essential to design flapping-wing micro air vehicles and to develop advanced controllers enhancing the autonomy of such vehicles. In this work, a phenomenological model is developed for the time-resolved aerodynamic forces on clap-and-fling ornithopters. The model is based on quasi-steady theory and accounts for inertial, circulatory, added mass and viscous forces. It extends existing quasi-steady approaches by: including a fling circulation factor to account for unsteady wing-wing interaction, considering real platform-specific wing kinematics and different flight regimes. The model parameters are estimated from wind tunnel measurements conducted on a real test platform. Comparison to wind tunnel data shows that the model predicts the lift forces on the test platform accurately, and accounts for wing-wing interaction effectively. Additionally, validation tests with real free-flight data show that lift forces can be predicted with considerable accuracy in different flight regimes. The complete parameter-varying model represents a wide range of flight conditions, is computationally simple, physically meaningful and requires few measurements. It is therefore potentially useful for both control design and preliminary conceptual studies for developing new platforms.

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Rigid-Body Kinematics Versus Flapping Kinematics of a Flapping Wing Micro Air Vehicle

Cited by 12 publications

References 25 publications

Onboard/Offboard Sensor Fusion for High-Fidelity Flapping-Wing Robot Flight Data

Onboard/Offboard Sensor Fusion for High-Fidelity Flapping-Wing Robot Flight Data

Longitudinal Grey-Box Model Identification of a Tailless Flapping-Wing MAV Based on Free-Flight Data

Quasi-steady aerodynamic model of clap-and-fling flapping MAV and validation using free-flight data

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