Laboratory-Scale Flight Characterization of a Multitethered Aerostat for Wind Energy Generation

Deodhar, Nihar; Bafandeh, Alireza; Deese, Joe; Smith, Brian; Muyimbwa, Tim; Vermillion, Chris; Tkacik, Peter T.

doi:10.2514/1.j054407

Cited by 14 publications

(19 citation statements)

References 17 publications

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“…These velocities correspond to flow velocities in the lab-scale platform described in Ref. [35]. Through the dimensional analysis discussed in Ref.…”

Section: External Perturbationmentioning

confidence: 83%

“…Moving forward, the aforementioned codesign framework will be extended to experimental codesign using the lab scale, water channel-based platform detailed in Ref. [35] at UNC-Charlotte. Thus, the results that are presented here provide a foundation for the extension to the experimental setup at UNC-Charlotte.…”

Section: Codesign Case Study On An Airborne Wind Energy Systemmentioning

confidence: 99%

“…Second, since the goal moving forward is an extension of this framework to an experimental codesign platform, the excitation should be implementable in the lab-scale environment described in Ref. [35]. In light of these requirements, a frequency approximation of vortex shedding off of a cylinder was used as the perturbation.…”

Section: External Perturbationmentioning

confidence: 99%

“…Through the dimensional analysis discussed in Ref. [35], these lab-scale flow velocities are equivalent to wind speeds of v base x ¼ 6:06 m=s; v x0 ¼ 0:866 m=s; v y0 ¼ 0:650 m=s; v z0 ¼ 0:0866 m=s (i.e., a scale factor of 10) and an oscillation frequency of x dist ¼ 0:2p rad=s (i.e., a scale factor of 1/10) on the full-scale BAT, which has 100 times the characteristic length of the models used in the lab-scale setup.…”

Section: External Perturbationmentioning

confidence: 99%

See 3 more Smart Citations

Nested Plant/Controller Codesign Using G-Optimal Design and Continuous Time Adaptation Laws: Theoretical Framework and Application to an Airborne Wind Energy System

Deese

Vermillion

2018

Journal of Dynamic Systems, Measurement, and Control

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This paper presents a nested codesign (combined plant and controller design) formulation that uses optimal design of experiments (DoE) techniques at the upper level to globally explore the plant design space, with continuous-time control parameter adaptation laws used at the lower level. The global design space exploration made possible through optimal DoE techniques makes the proposed methodology appealing for complex, nonconvex optimization problems for which legacy approaches are not effective. Furthermore, the use of continuous-time adaptation laws for control parameter optimization allows for the extension of the proposed optimization framework to the experimental realm, where control parameters can be optimized during experiments. At each full iteration, optimal DoE are used to generate a batch of plant designs within a prescribed design space. Each plant design is tested in either a simulation or experiment, during which an adaptation law is used for control parameter optimization. Two techniques are proposed for control parameter optimization at each iteration: extremum seeking (ES) and continuous-time DoE. The design space is reduced at the end of each full iteration, based on a response surface characterization and quality of fit estimate. The effectiveness of the approach is demonstrated for an airborne wind energy (AWE) system, where the plant parameters are the center of mass location and stabilizer area, and the control parameter is the trim pitch angle.

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“…These velocities correspond to flow velocities in the lab-scale platform described in Ref. [35]. Through the dimensional analysis discussed in Ref.…”

Section: External Perturbationmentioning

confidence: 83%

Section: Codesign Case Study On An Airborne Wind Energy Systemmentioning

confidence: 99%

Section: External Perturbationmentioning

confidence: 99%

Section: External Perturbationmentioning

confidence: 99%

See 2 more Smart Citations

Nested Plant/Controller Codesign Using G-Optimal Design and Continuous Time Adaptation Laws: Theoretical Framework and Application to an Airborne Wind Energy System

Deese

Vermillion

2018

Journal of Dynamic Systems, Measurement, and Control

Self Cite

View full text Add to dashboard Cite

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“…The authors of Refs. [17], [18], and [21][22][23][24], on the other hand, have developed a water channel-based framework for lab-scale experimental characterization of AWE systems, with the goal of establishing dynamic similarity results between this lab-scale setup and its full-scale counterpart. Work in Refs.…”

Section: Introductionmentioning

confidence: 99%

Lab-Scale Experimental Characterization and Dynamic Scaling Assessment for Closed-Loop Crosswind Flight of Airborne Wind Energy Systems

Cobb

Deodhar

Vermillion

2018

Journal of Dynamic Systems, Measurement, and Control

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This paper presents the experimental validation and dynamic similarity analysis for a lab-scale version of an airborne wind energy (AWE) system executing closed-loop motion control. Execution of crosswind flight patterns, achieved in this work through the asymmetric motion of three tethers, enables dramatic increases in energy generation compared with stationary operation. Achievement of crosswind flight in the lab-scale experimental framework described herein allows for rapid, inexpensive, and dynamically scalable characterization of new control algorithms without recourse to expensive full-scale prototyping. We first present the experimental setup, then derive dynamic scaling relationships necessary for the lab-scale behavior to match the full-scale behavior. We then validate dynamic equivalence of crosswind flight over a range of different scale models of the Altaeros Buoyant airborne turbine (BAT). This work is the first example of successful lab-scale control and measurement of crosswind motion for an AWE system across a range of flow speeds and system scales. The results demonstrate that crosswind flight can achieve significantly more power production than stationary operation, while also validating dynamic scaling laws under closed-loop control.

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Automatic testbed with a visual motion tracking system for airborne wind energy applications

et al. 2023

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The architecture and a flight test campaign of a small‐scale testbed aimed at aerodynamic and dynamic characterization of airborne wind energy systems are presented. The testbed involves a two‐line rigid‐framed delta kite and an automatic ground station for the lateral control of the kite and reel‐in/reel‐out of the two tethers. The environment, and the states of the kite, the tethers and the actuators are measured by a set of on‐ground and onboard sensors that include, among others, an inertial measurement unit, GNSS receivers, load cells, actuator encoders, a wind station, and a visual motion tracking (VMT) system based on three cameras and an artificial neural network (YOLOv2). The results of a 5‐min flight, including the take‐off, cross‐wind flight, and landing, were used to analyze the capabilities of the testbed. It was shown that the time derivative of the kite course angle exhibits a linear correlation with both the delayed steering input and the delayed differential tether tension, being the dispersion lower for the latter. The intrinsic and extrinsic calibrations proposed for the VMT system led to a good agreement between the estimation of the kite position and course angle provided by the VMT system and the onboard computer. Moreover, although the YOLOv2 algorithm failed in the detection of the kite within around 5% of the images, the simultaneous non‐detection from the three cameras was below 0.1% during the full flight. Such a reliability suggests that a VMT system can be used as a redundant or backup sensor for the GNSS.

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Laboratory-Scale Flight Characterization of a Multitethered Aerostat for Wind Energy Generation

Cited by 14 publications

References 17 publications

Nested Plant/Controller Codesign Using G-Optimal Design and Continuous Time Adaptation Laws: Theoretical Framework and Application to an Airborne Wind Energy System

Nested Plant/Controller Codesign Using G-Optimal Design and Continuous Time Adaptation Laws: Theoretical Framework and Application to an Airborne Wind Energy System

Lab-Scale Experimental Characterization and Dynamic Scaling Assessment for Closed-Loop Crosswind Flight of Airborne Wind Energy Systems

Automatic testbed with a visual motion tracking system for airborne wind energy applications

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