Modeling and Control of Flexible Wing with Trailing and Leading Edge Control Surfaces

2010 ◽  
Author(s):  
Dilmi Smain ◽  
Bouzouia Brahim
Keyword(s):  
Leading Edge ◽  
Modeling And Control ◽  
Flexible Wing ◽  
And Control ◽  
Control Surfaces

Marine Applications of the Biomimetic Humpback Whale Flipper

2011 ◽  
Vol 45 (4) ◽  
pp. 198-207 ◽  
Author(s):  
Frank E. Fish ◽  
Paul W. Weber ◽  
Mark M. Murray ◽  
Laurens E. Howle
Keyword(s):  
Leading Edge ◽  
Humpback Whale ◽  
Hydrodynamic Effect ◽  
Technological Advancement ◽  
Transfer Of Technology ◽  
Biomimetic Approach ◽  
Engineered Systems ◽  
Marine Applications ◽  
And Control ◽  
Control Surfaces

AbstractThe biomimetic approach seeks technological advancement through a transfer of technology from natural technologies to engineered systems. The morphology of the wing-like flipper of the humpback whale has potential for marine applications. As opposed to the straight leading edge of conventional hydrofoils, the humpback whale flipper has a number of sinusoid-like rounded bumps, called tubercles, which are arranged periodically along the leading edge. The presence of the tubercles modifies the water flow over the wing-like surface, creating regions of vortex generation between the tubercles. These vortices interact with the flow over the tubercle and accelerate that flow, helping to maintain a partially attached boundary layer. This hydrodynamic effect can delay stall to higher angles of attack, increases lift, and reduces drag compared to the post-stall condition of conventional wings. As the humpback whale functions in the marine environment in a Reynolds regime similar to some engineered marine systems, the use of tubercles has the potential to enhance the performance of wing-like structures. Specific applications of the tubercles for marine technology include sailboat masts, fans, propellers, turbines, and control surfaces, such as rudders, dive planes, stabilizers, spoilers, and keels.

Modeling and control of a flapping wing robot

2018 ◽  
Vol 233 (1) ◽  
pp. 174-181 ◽  
Author(s):  
Abdolbaghi Bakhtiari ◽  
Shahram Ehtemadi Haghighi ◽  
Adel Maghsoudpour
Keyword(s):  
Aerodynamic Force ◽  
Leading Edge ◽  
Flapping Wing ◽  
Inversion Method ◽  
Force Model ◽  
Modeling And Control ◽  
Theoretical Predictions ◽  
Dynamics And Control ◽  
Convergence Performance ◽  
And Control

The dynamics and control of a flapping wing robot are studied in this paper which helps to develop a complete dynamic model for the robot consisting of tail effects and also enhance the path tracking control of the robot. In the first part of the paper, the aerodynamic model of the wings is presented, and an aerodynamic force model for the tail is introduced which includes the leading edge suction effects. An experiment is also carried out on a flapping wing robot in a laboratory environment to evaluate the forces on the tail and its result will be compared with the results of the model presented for the tail. In the second part, a controller is designed for the robot. This controller uses the nonlinear dynamic inversion method to solve the nonlinear equations of the control system. The experimental results of the tail forces agree well with the theoretical predictions and reveal that the tail aerodynamics are affected by leading edge suction. Also, simulation results show that the competence performance and convergence performance of the designed controller are obtained.

Correction: Aeroelastic Modeling and Control of an Experimental Flexible Wing

2019 ◽  
Author(s):  
Manuel Pusch ◽  
Daniel Ossmann ◽  
Johannes Dillinger ◽  
Thiemo M. Kier ◽  
Martin Tang ◽  
...  
Keyword(s):  
Modeling And Control ◽  
Flexible Wing ◽  
And Control

scholarly journals Aeroelastic Modeling and Control of an Experimental Flexible Wing

2019 ◽  
Author(s):  
Manuel Pusch ◽  
Daniel Ossmann ◽  
Johannes Dillinger ◽  
Thiemo M. Kier ◽  
Martin Tang ◽  
...  
Keyword(s):  
Modeling And Control ◽  
Flexible Wing ◽  
And Control

Modeling and Control for Plant Dynamics Based on Reinforcement Learning

2009 ◽  
Vol 129 (4) ◽  
pp. 363-367
Author(s):  
Tomoyuki Maeda ◽  
Makishi Nakayama ◽  
Hiroshi Narazaki ◽  
Akira Kitamura
Keyword(s):  
Reinforcement Learning ◽  
Modeling And Control ◽  
Plant Dynamics ◽  
And Control
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