Aeroelastic Simulation of Flexible Membrane Wings based on Multibody System Dynamics

Breukels, J.; Schmehl, Roland; Ockels, Wubbo

doi:10.1007/978-3-642-39965-7_16

Cited by 24 publications

(25 citation statements)

References 4 publications

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“…a wing) attached to a fixed point by a fixedlength tether. A wealth of information on modeling kite dynamics has become available in the last decade [17,28,15,7,20,24,25,8,6,18]. Models can be constructed with anything from 3 to several hundred states.…”

Section: Modelingmentioning

confidence: 99%

“…Control design and optimization are usually performed using simplified dynamic models that are more computationally tractable and intuitive. However, it is well known that accurately modeling a kite behavior requires extremely detailed models [24,8], and these simplified models are unavoidably inaccurate. Even early in the field of kite control, this motivated the design of robust control strategies, see for example [27,30].…”

Section: Introductionmentioning

confidence: 99%

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Crosswind kite control – A benchmark problem for advanced control and dynamic optimization

Costello

François

Bonvin

2017

European Journal of Control

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This article presents a kite control and optimization problem intended as a benchmark problem for advanced control and optimization. We provide an entry point to this exciting renewable energy system for researchers in control and optimization methods looking for a realistic test bench, and/or a useful application case for their theory. The benchmark problem in this paper can be studied in simulation, and a complete Simulink model is provided to facilitate this. The simulated scenario, which reproduces many of the challenges presented by a real system, is based on experimental studies from the literature, industrial data and the first author's own experience in experimental kite control. In particular, an experimentally validated wind turbulence model is included, which subjects the kite to realistic disturbances. The benchmark problem is that of controlling a kite such that the average line tension is maximized. Two different models are provided: A more comprehensive one is used to simulate the 'plant', while a simpler 'model' is used to design and implement control and optimization strategies. This way, uncertainty is present in the form of plant-model mismatch. The outputs of the plant are corrupted by measurement noise. The maximum achievable average line tension for the plant is calculated, which should facilitate the performance comparison of different algorithms. A simple control strategy is implemented on the plant and found to be quite sub-optimal, even if the free parameters of the algorithm are well tuned. An open question is whether or not more advanced control algorithms could do better. * Dr. Costello (sean.c.costello@gmail.com)

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Section: Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Crosswind kite control – A benchmark problem for advanced control and dynamic optimization

Costello

François

Bonvin

2017

European Journal of Control

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“…Small-scale prototypes (10-50 kW of rated power) of the mentioned concepts have been realized and successfully tested to demonstrate their power generation functionalities. Moreover, scientific contributions concerned with technical aspects like aerodynamics [10,11,9,16,25], controls [24,12,6,14,21,17,22,34,13,35], resource assessment [5,4], economics [20,36], prototype design [18], and power conversion [30], have recently appeared, gradually improving and expanding our understanding of such systems.…”

Section: Introductionmentioning

confidence: 99%

On the autonomous take-off and landing of tethered wings for airborne wind energy

Van

Fagiano

Schnez

2016

2016 American Control Conference (ACC)

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The problem of autonomous launch and landing of a tethered rigid aircraft for airborne wind energy generation is addressed. The system operates with ground-based power conversion and pumping cycles, where the tether is repeatedly reeled in and out of a winch installed on the ground and linked to an electric motor/generator. In order to accelerate the aircraft to take-off speed, the ground station is augmented with a linear motion system composed by a slide translating on rails and controlled by a second motor. An onboard propeller is used to sustain the forward velocity during the ascend of the aircraft. During landing, a slight tension on the line is kept, while the onboard control surfaces are used to align the aircraft with the rails and to land again on them. A model-based, decentralized control approach is proposed, capable to carry out a full cycle of launch, low-tension flight, and landing again on the rails. The derived controller is tested via numerical simulations with a realistic dynamical model of the system, in presence of different wind speeds and turbulence, and its performance in terms of landing accuracy is assessed. This study is part of a project aimed to experimentally verify the launch and landing approach on a small-scale prototype.

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“…Much progress has been made in modeling the dynamics of flexible kites during the last decade [9], [21], [31], [32], [33], [13], [34], [12], [35], [36]. Relatively simple tendency models have between 3 and 10 states, while more complex models aimed at achieving great precision have up to several hundred states.…”

Section: Modelingmentioning

confidence: 99%

“…Unfortunately, this has yet to become a practical reality, mainly due to the inaccuracy of existing kite models, as NMPC relies on the quality of the model at hand. Many power kites are of the flexible kind, and accurate models [12], [13] are very complex, generally unsuitable for NMPC. We note, however, that with recent advances in MPC [14], this situation will hopefully change.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

Costello

François

Bonvin

2018

IEEE Trans. Contr. Syst. Technol.

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Abstract-The contribution of this article is to propose and experimentally validate an optimizing control strategy for power kites flying crosswind. The algorithm ensures the kite follows a reference path (control) and also periodically optimizes the reference path (efficiency optimization). The path-following part of the controller is capable of consistently following a reference path, despite significant time delays and wind variations, using position measurements only. The path-optimization part adjusts the reference path in order to maximize line tension. It uses a real-time optimization algorithm that combines off-line modeling knowledge and on-line measurements. The algorithm has been tested comprehensively on a small-scale prototype, and this article focuses on experimental results.

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Aeroelastic Simulation of Flexible Membrane Wings based on Multibody System Dynamics

Cited by 24 publications

References 4 publications

Crosswind kite control – A benchmark problem for advanced control and dynamic optimization

Crosswind kite control – A benchmark problem for advanced control and dynamic optimization

On the autonomous take-off and landing of tethered wings for airborne wind energy

Real-Time Optimizing Control of an Experimental Crosswind Power Kite

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