Model-based flight path planning and tracking for tethered wings

In this paper we propose a guidance strategy for the flight control of a tethered wing. We control the wing trajectory in a cascaded approach via the velocity vector orientation. In particular, we consider a control-oriented model with an input delay to follow a reference path. To account for the delay we design a predictor and use the predictions to compute a reference for a lower level tracking controller. In a path-planning step we design reference figure-eight paths for the wing to follow. The path design explicitly considers the model parameters used in the tracking controller such that limitations induced by the delay are respected. By estimating the model parameters on-line we enable the adaptation of the tracking controller and also the path-planner to time varying conditions, including the input delay and crucially the line length. We present the derivation of the guidance strategy and demonstrate its performance via simulation results.

[1]  Colin Neil Jones,et al.  Improved path following for kites with input delay compensation , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[2]  Mario Zanon,et al.  A relaxation strategy for the optimization of Airborne Wind Energy systems , 2013, 2013 European Control Conference (ECC).

[3]  O. J. M. Smith,et al.  A controller to overcome dead time , 1959 .

[4]  M. L. Loyd,et al.  Crosswind kite power (for large-scale wind power production) , 1980 .

[5]  Roland Schmehl,et al.  Applied Tracking Control for Kite Power Systems , 2014 .

[6]  Sebastian Engell,et al.  Control of towing kites under uncertainty using robust economic nonlinear model predictive control , 2014, 2014 European Control Conference (ECC).

[7]  Lorenzo Fagiano,et al.  Real-Time Optimization and Adaptation of the Crosswind Flight of Tethered Wings for Airborne Wind Energy , 2013, IEEE Transactions on Control Systems Technology.

[8]  Lorenzo Fagiano,et al.  Automatic Crosswind Flight of Tethered Wings for Airborne Wind Energy: Modeling, Control Design, and Experimental Results , 2013, IEEE Transactions on Control Systems Technology.

[9]  Lorenzo Fagiano,et al.  On Sensor Fusion for Airborne Wind Energy Systems , 2012, IEEE Transactions on Control Systems Technology.

[10]  Aldo U. Zgraggen,et al.  Model-based identification and control of the velocity vector orientation for autonomous kites , 2015, 2015 American Control Conference (ACC).

[11]  Paul Williams,et al.  Nonlinear Control and Estimation of a Tethered Kite in Changing Wind Conditions , 2008 .

[12]  Tony A. Wood,et al.  Range-inertial estimation for airborne wind energy , 2015, 2015 54th IEEE Conference on Decision and Control (CDC).

[13]  Lorenzo Fagiano,et al.  Automatic Retraction Phase of Airborne Wind Energy Systems , 2014 .

[14]  Michael Erhard,et al.  Flight control of tethered kites in autonomous pumping cycles for airborne wind energy , 2015 .

[15]  Manfred Morari,et al.  Smith Predictor Design for Robust Performance , 1987, 1987 American Control Conference.

[16]  Mario Zanon,et al.  Control of Rigid-Airfoil Airborne Wind Energy Systems , 2013 .

[17]  Ian Postlethwaite,et al.  Multivariable Feedback Control: Analysis and Design , 1996 .

[18]  Rolf H. Luchsinger,et al.  Simulation Based Wing Design for Kite Power , 2013 .

[19]  Moritz Diehl,et al.  Nonlinear MPC of kites under varying wind conditions for a new class of large‐scale wind power generators , 2007 .

[20]  Damon Vander Lind Analysis and Flight Test Validation of High Performance AirborneWind Turbines , 2013 .

[21]  Mario Zanon,et al.  Model Predictive Control of Rigid-Airfoil Airborne Wind Energy Systems , 2013 .

[22]  Michael Erhard,et al.  Theory and Experimental Validation of a Simple Comprehensible Model of Tethered Kite Dynamics Used for Controller Design , 2013 .

[23]  Lorenzo Fagiano,et al.  High Altitude Wind Energy Generation Using Controlled Power Kites , 2010, IEEE Transactions on Control Systems Technology.