Sensors and Navigation Algorithms for Flight Control of Tethered Kites

We present the sensor setup and the basic navigation algorithm used for the flight control of the SkySails towing kite system. Starting with brief summaries on system setup and equations of motion of the tethered kite system, we subsequently give an overview of the sensor setup, present the navigation task and discuss challenges which have to be mastered. In the second part we introduce in detail the inertial navigation algorithm which has been used for operational flights for years. The functional capability of this algorithm is illustrated by experimental flight data. Finally we suggest a modification of the algorithms as further development step in order to overcome certain limitations.Comment: 6 pages, 9 figures, submitted to European Control Conference (ECC) 201

On sensor fusion for airborne wind energy systems

A study on filtering aspects of airborne wind energy generators is presented. This class of renewable energy systems aims to convert the aerodynamic forces generated by tethered wings, flying in closed paths transverse to the wind flow, into electricity. The accurate reconstruction of the wing's position, velocity and heading is of fundamental importance for the automatic control of these kinds of systems. The difficulty of the estimation problem arises from the nonlinear dynamics, wide speed range, large accelerations and fast changes of direction that the wing experiences during operation. It is shown that the overall nonlinear system has a specific structure allowing its partitioning into sub-systems, hence leading to a series of simpler filtering problems. Different sensor setups are then considered, and the related sensor fusion algorithms are presented. The results of experimental tests carried out with a small-scale prototype and wings of different sizes are discussed. The designed filtering algorithms rely purely on kinematic laws, hence they are independent from features like wing area, aerodynamic efficiency, mass, etc. Therefore, the presented results are representative also of systems with larger size and different wing design, different number of tethers and/or rigid wings.Comment: This manuscript is a preprint of a paper accepted for publication on the IEEE Transactions on Control Systems Technology and is subject to IEEE Copyright. The copy of record is available at IEEEXplore library: http://ieeexplore.ieee.org

State Estimation for Kite Power Systems with Delayed Sensor Measurements

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

Control of Towing Kites for Seagoing Vessels

In this paper we present the basic features of the flight control of the SkySails towing kite system. After introduction of coordinate definitions and basic system dynamics we introduce a novel model used for controller design and justify its main dynamics with results from system identification based on numerous sea trials. We then present the controller design which we successfully use for operational flights for several years. Finally we explain the generation of dynamical flight patterns.Comment: 12 pages, 18 figures; submitted to IEEE Trans. on Control Systems Technology; revision: Fig. 15 corrected, minor text change

Visual motion tracking and sensor fusion for kite power systems

An estimation approach is presented for kite power systems with groundbased actuation and generation. Line-based estimation of the kite state, including position and heading, limits the achievable cycle efficiency of such airborne wind energy systems due to significant estimation delay and line sag. We propose a filtering scheme to fuse onboard inertial measurements with ground-based line data for ground-based systems in pumping operation. Estimates are computed using an extended Kalman filtering scheme with a sensor-driven kinematic process model which propagates and corrects for inertial sensor biases. We further propose a visual motion tracking approach to extract estimates of the kite position from ground-based video streams. The approach combines accurate object detection with fast motion tracking to ensure long-term object tracking in real time. We present experimental results of the visual motion tracking and inertial sensor fusion on a ground-based kite power system in pumping operation and compare both methods to an existing estimation scheme based on line measurements