Adaptive control for bioinspired flapping wing robots

Bayandor, Javid; Bledt, Gerardo; Dadashi, Shirin; Kurdila, Andrew J.; Murphy, I.; Yu, Lei

doi:10.1109/acc.2013.6579904

Cited by 10 publications

(2 citation statements)

References 15 publications

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“…The advances in computational modeling and resulting aerodynamic understanding of complex flight phenomenon is directly aiding the development of robotic MAV systems ( Wood et al, 2013 ). There have been multiple attempts to create low-order models approximating more complex computational fluid dynamics (CFD) results, which could be implemented into various control schemes ( Amiralaei et al, 2012 ; Singh et al, 2004 ; Taha et al, 2014 ; Bayandor et al, 2013 ; Dadashi et al, 2016 ).…”

Section: Introductionmentioning

confidence: 99%

A computational study on the influence of insect wing geometry on bee flight mechanics

2017

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Two-dimensional computational fluid dynamics (CFD) is applied to better understand the effects of wing cross-sectional morphology on flow field and force production. This study investigates the influence of wing cross-section on insect scale flapping flight performance, for the first time, using a morphologically representative model of a bee (Bombus pensylvanicus) wing. The bee wing cross-section was determined using a micro-computed tomography scanner. The results of the bee wing are compared with flat and elliptical cross-sections, representative of those used in modern literature, to determine the impact of profile variation on aerodynamic performance. The flow field surrounding each cross-section and the resulting forces are resolved using CFD for a flight speed range of 1 to 5 m/s. A significant variation in vortex formation is found when comparing the ellipse and flat plate with the true bee wing. During the upstroke, the bee and approximate wing cross-sections have a much shorter wake structure than the flat plate or ellipse. During the downstroke, the flat plate and elliptical cross-sections generate a single leading edge vortex, while the approximate and bee wings generate numerous, smaller structures that are shed throughout the stroke. Comparing the instantaneous aerodynamic forces on the wing, the ellipse and flat plate sections deviate progressively with velocity from the true bee wing. Based on the present findings, a simplified cross-section of an insect wing can misrepresent the flow field and force production. We present the first aerodynamic study using a true insect wing cross-section and show that the wing corrugation increases the leading edge vortex formation frequency for a given set of kinematics.

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Section: Introductionmentioning

confidence: 99%

A computational study on the influence of insect wing geometry on bee flight mechanics

2017

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“…Even a wing design and optimization tool is available [6] for the researchers. Different control approaches were used for control of the vehicles -ranging from simple open loop control [7], through classical control [8,9], modern control [10], and adaptive control [11], to vision based control systems [12].…”

Section: Introductionmentioning

confidence: 99%

An Evolutionary Approach to Tuning a Multi-Agent System for Autonomous Adaptive Control of a Flapping-Wing Micro Air Vehicle

Podhradský

Greenwood

2016

Int. J. Robot. Autom. Technol.

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Biomimetic flapping wing vehicles have attracted recent interest because of their numerous potential military and civilian applications. In this paper, we describe an evolutionary approach to tuning a Multi-Agent System for autonomous adaptive control of a Flapping-Wing Micro Air Vehicle. The wings of the vehicle are controlled by a split cycle oscillator, which combined with non-linearities and differences between each vehicle, brings significant challenge for selecting the proper parameters for the control system. Adopting a Neo-Darwinistic evolutionary approach, where solutions are evolved in a similar manner as in nature, allows us to precisely learn control parameters for each vehicle. After describing the evolution algorithm and evolving the control parameters, we utilize these values for autonomous waypoint following by the micro air vehicle.

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Distribution-free learning theory for approximating submanifolds from reptile motion capture data

Powell

Kurdila

2021

Comput Mech

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Adaptive control for bioinspired flapping wing robots

Cited by 10 publications

References 15 publications

A computational study on the influence of insect wing geometry on bee flight mechanics

A computational study on the influence of insect wing geometry on bee flight mechanics

An Evolutionary Approach to Tuning a Multi-Agent System for Autonomous Adaptive Control of a Flapping-Wing Micro Air Vehicle

Distribution-free learning theory for approximating submanifolds from reptile motion capture data

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