13,112 research outputs found
Predictive Control of Autonomous Kites in Tow Test Experiments
In this paper we present a model-based control approach for autonomous flight
of kites for wind power generation. Predictive models are considered to
compensate for delay in the kite dynamics. We apply Model Predictive Control
(MPC), with the objective of guiding the kite to follow a figure-of-eight
trajectory, in the outer loop of a two level control cascade. The tracking
capabilities of the inner-loop controller depend on the operating conditions
and are assessed via a frequency domain robustness analysis. We take the
limitations of the inner tracking controller into account by encoding them as
optimisation constraints in the outer MPC. The method is validated on a kite
system in tow test experiments.Comment: The paper has been accepted for publication in the IEEE Control
Systems Letters and is subject to IEEE Control Systems Society copyright.
Upon publication, the copy of record will be available at
http://ieeexplore.ieee.or
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
Peak Estimation of Rational Systems using Convex Optimization
This paper presents algorithms that upper-bound the peak value of a state
function along trajectories of a continuous-time system with rational dynamics.
The finite-dimensional but nonconvex peak estimation problem is cast as a
convex infinite-dimensional linear program in occupation measures. This
infinite-dimensional program is then truncated into finite-dimensions using the
moment-Sum-of-Squares (SOS) hierarchy of semidefinite programs. Prior work on
treating rational dynamics using the moment-SOS approach involves clearing
dynamics to common denominators or by adding lifting variables to handle
reciprocal terms under new equality constraints. Our solution method uses a
sum-of-rational method based on absolute continuity of measures. The Moment-SOS
truncations of our program possess lower computational complexity and
(empirically demonstrated) higher accuracy of upper bounds on example systems
as compared to prior approaches.Comment: 8 pages, 2 figures, 2 table
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