Model-based identification and control of the velocity vector orientation for autonomous kites

Wood, Tony; Hesse, Henrik; Zgraggen, Aldo U.; Smith, Roy S.

doi:10.1109/acc.2015.7171088

Cited by 18 publications

(51 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kite state estimation given output delay is addressed in Polzin et al (2017). In Wood et al (2015a) the estimated kite heading angle was related to the steering input with a model that includes an input delay. This model was applied to improve the tracking performance in the inner loop of the cascaded control approach in Fagiano et al (2014).…”

Section: Introductionmentioning

confidence: 99%

“…Kinematic models have been proposed in Rontsis et al (2015); Erhard and Strauch (2013b); Wood et al (2015b) to further link the kite heading angle to the overall kite motion. In Rontsis et al (2015) a kinematic model was used to develop a delay-compensating path controller which was experimentally demonstrated for constant line length.…”

Section: Introductionmentioning

confidence: 99%

“…In Rontsis et al (2015) a kinematic model was used to develop a delay-compensating path controller which was experimentally demonstrated for constant line length. Wood et al (2015b) also used a kinematic model including input delay to further improve the outer loop of the control approach in Fagiano et al (2014). The proposed method includes a figure-of-eight path planning strategy in which limitations on the tracking bandwidth imposed by the input delay are considered.…”

Section: Introductionmentioning

confidence: 99%

“…In this work, we extend the guidance strategy in Wood et al (2015b) by formulating an optimisation problem with constraints on the input, input rate, and on the kite position. Respecting the input rate constraint in the cascaded control architecture ensures robust tracking performance of the underlying controller.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Predictive Guidance Control for Autonomous Kites with Input Delay

et al. 2017

Self Cite

View full text Add to dashboard Cite

Abstract:We consider the design of a model predictive guidance controller in a cascaded control scheme for an autonomous kite with significant input delay. The rate of change of the signal commanded by the guidance is bounded to ensure robust performance of the underlying tracking controller. We analyse the limitations of the tracking controller arising from model parameter uncertainty and input delay. The delay is accounted for in the control design by predicting the values of the feedback variables ahead of time based on the past inputs and the system models. To account for changing operating conditions the model parameters are updated online. The proposed method has been tested in a real-time hardware-in-the-loop simulation study.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Predictive Guidance Control for Autonomous Kites with Input Delay

et al. 2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…For wings without depowering capabilities this assumption also holds in retraction phases. A unicycle model has been applied to model the motion of a wing on the surface of a sphere by Erhard and Strauch (2013a) and Wood et al (2015b). The corresponding kinematic equations arė…”

Section: Unicycle Modelmentioning

confidence: 99%

State Estimation for Kite Power Systems with Delayed Sensor Measurements

et al. 2017

Self Cite

View full text Add to dashboard Cite

We present a novel estimation approach for airborne wind energy systems with ground-based control and energy generation. The estimator fuses measurements from an inertial measurement unit attached to a tethered wing and position measurements from a camera as well as line angle sensors in an unscented Kalman filter. We have developed a novel kinematic description for tethered wings to specifically address tether dynamics. The presented approach simultaneously estimates feedback variables for a flight controller as well as model parameters, such as a time-varying delay. We demonstrate the performance of the estimator for experimental flight data and compare it to a state-of-the-art estimator based on inertial measurements.

show abstract

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

et al. 2023

View full text Add to dashboard Cite

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.

show abstract

Model-based identification and control of the velocity vector orientation for autonomous kites

Cited by 18 publications

References 7 publications

Predictive Guidance Control for Autonomous Kites with Input Delay

Predictive Guidance Control for Autonomous Kites with Input Delay

State Estimation for Kite Power Systems with Delayed Sensor Measurements

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

Contact Info

Product

Resources

About