Warping model predictive control for application in control of a real airborne wind energy system

Abstract Fast online generation of feasible and optimal reference trajectories is crucial in tracking model predictive control, especially for stability and optimality in presence of a time varying parameter. In this paper, in order to circumvent the operational efforts of handling a discrete set of precomputed trajectories and switching between them, time warping of a single trajectory is proposed as an alternative concept. In particular, the conceptual ideas of warping theory are presented and illustrated based on the example of a tethered kite system for airborne wind energy. In detail, for warpable systems, feasibility and optimality of trajectories are discussed. Subsequently, the full algorithm of a nonlinear model predictive control implementation based on warping a single precomputed reference is presented. Finally, the warping algorithm is applied to the airborne wind energy system. Simulation results in presence of real world perturbations are evaluated and compared.

[1]  Denis Dochain,et al.  Warping NMPC for Online Generation and Tracking of Optimal Trajectories , 2017 .

[2]  Moritz Diehl,et al.  A quaternion‐based model for optimal control of an airborne wind energy system , 2015, ArXiv.

[3]  Anthony Tzes,et al.  On Trajectory Tracking Model Predictive Control of an Unmanned Quadrotor Helicopter Subject to Aerodynamic Disturbances , 2014 .

[4]  L. Grüne,et al.  Nonlinear Model Predictive Control : Theory and Algorithms. 2nd Edition , 2011 .

[5]  Rita Cunha,et al.  Trajectory Tracking Nonlinear Model Predictive Control for Autonomous Surface Craft , 2009, IEEE Transactions on Control Systems Technology.

[6]  Jan Poland,et al.  Nonlinear coal mill modeling and its application to model predictive control , 2013 .

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

[8]  Lorenz T. Biegler,et al.  On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming , 2006, Math. Program..

[9]  M. Diehl,et al.  Airborne Wind Energy , 2023, Green Energy and Technology.

[10]  Joel Andersson,et al.  A General-Purpose Software Framework for Dynamic Optimization (Een algemene softwareomgeving voor dynamische optimalisatie) , 2013 .

[11]  M. L. Loyd.  Crosswind kite power , 1980 .

[12]  Michael Erhard,et al.  Control of Towing Kites for Seagoing Vessels , 2012, IEEE Transactions on Control Systems Technology.

[13]  Dario Piga,et al.  Optimization of airborne wind energy generators , 2012 .

[14]  Chris Manzie,et al.  Model reduction and MIMO model predictive control of gas turbine systems , 2015 .

[15]  James B. Rawlings,et al.  Optimizing Process Economic Performance Using Model Predictive Control , 2009 .

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

[17]  Abhishek Dutta,et al.  Comparison of two-level NMPC and ILC strategies for wet-clutch control , 2014 .

[18]  Peter B. Luh,et al.  Nested partitions for global optimization in nonlinear model predictive control , 2012 .

[19]  H. Bock,et al.  A Multiple Shooting Algorithm for Direct Solution of Optimal Control Problems , 1984 .

[20]  Mario Zanon,et al.  A tracking MPC formulation that is locally equivalent to economic MPC , 2016 .

[21]  Zoltan K. Nagy,et al.  Evaluation study of an efficient output feedback nonlinear model predictive control for temperature tracking in an industrial batch reactor , 2007 .