Proof of Well-Posedness for a Flexible-Wing Micro Air Vehicle Model Control Problem Incorporating Spatial Hysteresis

2019 ◽  
Author(s):  
Jonathan B. Walters ◽  
Katie A. Evans
Keyword(s):  
Control Problem ◽  
Micro Air Vehicle ◽  
Well Posedness ◽  
Vehicle Model ◽  
Flexible Wing ◽  
Model Control ◽  
Air Vehicle

scholarly journals Dove: A biomimetic flapping-wing micro air vehicle

2017 ◽  
Vol 10 (1) ◽  
pp. 70-84 ◽  
Author(s):  
Wenqing Yang ◽  
Liguang Wang ◽  
Bifeng Song
Keyword(s):  
Mechanism Design ◽  
Flapping Wing ◽  
Micro Air Vehicle ◽  
Flexible Wing ◽  
The Past ◽  
Ground Station ◽  
Air Vehicle ◽  
Research Goal ◽  
Color Video ◽  
Flapping Mechanism

This paper describes the design and development of the Dove, a flapping-wing micro air vehicle (FWMAV), which was developed in Northwestern Polytechnical University. FWMAVs have attracted international attentions since the past two decades. Since some achievements have been obtained, such as the capability of supporting an air vehicle to fly, our research goal was to design an FWMAV that has the ability to accomplish a task. Main investigations were presented in this paper, including the flexible wing design, the flapping mechanism design, and the on-board avionics development. The current Dove has a mass of 220 g, a wingspan of 50 cm, and the ability of operating fully autonomously, flying lasts half an hour, and transmitting live stabilized color video to a ground station over 4 km away.

Improving In-Flight Learning in a Flapping Wing Micro Air Vehicle

2016 ◽  
Vol 4 (1) ◽  
pp. 62-75
Author(s):  
Monica Sam ◽  
Sanjay Boddhu ◽  
Kayleigh Duncan ◽  
Hermanus Botha ◽  
John Gallagher
Keyword(s):  
Evolutionary Algorithms ◽  
Control Problem ◽  
Flight Control ◽  
Search Space ◽  
Flapping Wing ◽  
Micro Air Vehicle ◽  
Flight Trajectory ◽  
Air Vehicle ◽  
Major Criterion ◽  
Sampling Approach

Much effort has gone into improving the performance of evolutionary algorithms that augment traditional control in a Flapping Wing Micro Air Vehicle. An EA applied to such a vehicle in flight is expected to evolve solutions quickly to prevent disruptions in following the desired flight trajectory. Time to evolve solutions therefore is a major criterion by which performance of an algorithm is evaluated. This paper presents results of applying an assortment of different evolutionary algorithms to the problem. This paper also presents some discussion on which choices for representation and algorithm parameters would be optimal for the flight control problem and the rationale behind it. The authors also present a guided sampling approach of the search space to make use of the redundancy of workable solutions found in the search space. This approach has been demonstrated to improve learning times when applied to the problem.

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