Engineless Unmanned Aerial Vehicle Propulsion by Dynamic Soaring

Deittert, Markus; Richards, Arthur; Toomer, Chris; Pipe, Anthony G.

doi:10.2514/1.43270

Cited by 99 publications

(96 citation statements)

References 11 publications

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“…The generation of a Rayleigh cycle is generally transformed into an optimal trajectory problem, which has been solved by many numerical optimization methods such as the Gauss pseudo-spectral method of the optimal software called Gauss Pseudospectral Optimization Software (GPOPS) [24][25][26][27][28]. The optimized trajectory should satisfy the dynamics Equations (4)- (8), and the performance function gives the total energy harvest in a cycle, expressed as…”

Section: Optimization Methods For Generating Rayleigh Cyclementioning

confidence: 99%

“…The wind gradient thus causes the albatross to gain extra airspeed, which is transformed into an inertial force, referred to as a dynamic soaring thrust. The dynamic model can be directly taken from Deittert's [27] or Gao's [36] work as follows:…”

Section: Dynamic Modelmentioning

confidence: 99%

“…Although the optimization method affords an optimal means of generating a Rayleigh Cycle [18][19][20][21][22][23][24][25][26][27][28], the computation procedure, as noted above, is too time-consuming for real-time applications. Hence, we used a state machine to imitate the four phases of the Rayleigh cycle of an albatross, namely, the upwind climb, high-altitude turn, downwind dive, and low-altitude turn phases.…”

Section: Bio-inspired Strategymentioning

confidence: 99%

“…Kaushik et al [24] used the GPOPS-II optimal control software for trajectory computation. There have been several other studies on the optimization of dynamic soaring [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

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Albatross-Like Utilization of Wind Gradient for Unpowered Flight of Fixed-Wing Aircraft

2017

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Abstract:The endurance of an aircraft can be considerably extended by its exploitation of the hidden energy of a wind gradient, as an albatross does. The process is referred to as dynamic soaring and there are two methods for its implementation, namely, sustainable climbing and the Rayleigh cycle. In this study, the criterion for sustainable climbing was determined, and a bio-inspired method for implementing the Rayleigh cycle in a shear wind was developed. The determined sustainable climbing criterion promises to facilitate the development of an unpowered aircraft and the choice of a more appropriate soaring environment, as was demonstrated in this study. The criterion consists of three factors, namely, the environment, aerodynamics, and wing loading. We develop an intuitive explanation of the Raleigh cycle and analyze the energy mechanics of utilizing a wind gradient in unpowered flight. The energy harvest boundary and extreme power point were determined and used to design a simple bio-inspired guidance strategy for implementing the Rayleigh cycle. The proposed strategy, which involves the tuning of a single parameter, can be easily implemented in real-time applications. In the results and discussions, the effects of each factor on climbing performance are examined and the sensitivity of the aircraft factor is discussed using five examples. Experimental MATLAB simulations of the proposed strategy and the comparison of the results with those of Gauss Pseudospectral Optimization Software confirm the feasibility of the proposed strategy.

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Section: Optimization Methods For Generating Rayleigh Cyclementioning

confidence: 99%

Section: Dynamic Modelmentioning

confidence: 99%

Section: Bio-inspired Strategymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Albatross-Like Utilization of Wind Gradient for Unpowered Flight of Fixed-Wing Aircraft

2017

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“…V soaring is exploited in unmanned aerial vehicles (UAVs) and gives them an energy-free loitering and traveling capability that prolongs their endurance [2]. Energy-optimal trajectories for UAVs equipped with solar cells are considered in [3].…”

Section: Vehicular Optimal Controlmentioning

confidence: 99%

Faster, Higher, and Greener: Vehicular Optimal Control

Limebeer

Rao

2015

IEEE Control Syst.

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Disturbance rejection enhancement using predictive control for the fixed‐wing UAV with multiple ailerons

Sattar

Wang

Ansari

et al. 2023

Adaptive Control & Signal

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Summary The performance of small fixed‐wing unmanned aerial vehicles (UAVs) is easily degraded by exogenous disturbances. In an attempt to improve the performance, the structural change is made in conventional small fixed‐wing UAV through segmentation of each aileron control surface into multiples. Detailed system identification experiments are performed on each aileron pair in the wind tunnel to acquire linear dynamic models for the roll attitude of the UAV. These experiments have provided the transfer functions for the aileron control surfaces based on corresponding frequency response. Three distinctive model predictive controllers are designed and deployed in real‐time hardware to achieve the roll attitude control. The roll attitude control experiments are validated in wind tunnel under both normal and turbulent environments. The results show that multiple input and single output control system provides significant improvement in the roll attitude and disturbance rejection performance. The collective actuation of multiple control surfaces improves roll stability by 10.1%$$ 10.1\% $$ to 67.87%$$ 67.87\% $$ when compared to the single aileron pair based conventional control in the presence of turbulent flight conditions.

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Engineless Unmanned Aerial Vehicle Propulsion by Dynamic Soaring

Cited by 99 publications

References 11 publications

Albatross-Like Utilization of Wind Gradient for Unpowered Flight of Fixed-Wing Aircraft

Albatross-Like Utilization of Wind Gradient for Unpowered Flight of Fixed-Wing Aircraft

Faster, Higher, and Greener: Vehicular Optimal Control

Disturbance rejection enhancement using predictive control for the fixed‐wing UAV with multiple ailerons

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