Litcius/Paper detail

Nonlinear Model Predictive Velocity Control of a VTOL Tiltwing UAV

David Rohr, Matthias Studiger, Thomas Stastny, Nicholas Lawrance, Roland Siegwart

2021IEEE Robotics and Automation Letters47 citationsDOIOpen Access PDF

Abstract

This letter presents the modeling, system identification and nonlinear model predictive control (NMPC) design for longitudinal, full envelope velocity control of a small tiltwing hybrid unmanned aerial vehicle (H-UAV). A first-principles based dynamics model is derived and identified from flight data. It captures important aerodynamic effects including propeller-wing interaction and stalled airfoils, but is still simple enough for on-board online trajectory optimization. Based on this model, a high-level NMPC is formulated which optimizes throttle, tilt-rate and pitch-angle setpoints in order to track longitudinal velocity trajectories. We propose and investigate different references suitable to regularize the optimization problem, including both offline generated trims as well as preceding NMPC solutions. In simulation, we compare the NMPC with a frequently reported dynamic inversion approach for H-UAV velocity control. Finally, the NMPC is validated in flight experiments through a series of transition maneuvers, demonstrating good tracking capabilities in the full flight envelope.

Topics & Concepts

Control theory (sociology)Model predictive controlAerodynamicsNonlinear systemNonlinear modelFlight envelopeAngle of attackTrajectoryEngineeringComputer scienceAerospace engineeringControl (management)PhysicsArtificial intelligenceQuantum mechanicsAstronomyAdvanced Control Systems OptimizationAdaptive Control of Nonlinear SystemsStability and Control of Uncertain Systems