Economic Model-Predictive Control Strategies for Aircraft Deep-stall Recovery with Stability Guarantees

Torbjørn Cunis (1, 2) , Dominic Liao-Mcpherson (3) , Jean-Philippe Condomines (2) , Laurent Burlion (4) , Ilya Kolmanovsky (3)

1 DTIS, ONERA, Université de Toulouse [Toulouse]
2 ENAC - Ecole Nationale de l'Aviation Civile
3 University of Michigan [Ann Arbor]
4 RU - Rutgers, The State University of New Jersey [New Brunswick]

Aircraft upset recovery requires aggressive control actions to handle highly nonlinear aircraft dynamics and critical state and input constraints. Model predictive control is a promising approach for returning the aircraft to the nominal flight envelope, even in the presence of altered dynamics or actuator limits; however, proving stability of such strategies requires careful algebraic or semi-algebraic analysis of both the system and the proposed control scheme, which can be challenging for realistic control systems. This paper develops economic model predictive strategies for recovery of a fixed-wing aircraft from deep-stall. We provide rigorous stability proofs using sum-of-squares programming and compare several economic, nonlinear, and linear model predictive controllers .

Domaines: Systèmes et contrôle [cs.SY]; Automatique / Robotique

Torbjørn Cunis, Dominic Liao-Mcpherson, Jean-Philippe Condomines, Laurent Burlion, Ilya Kolmanovsky. Economic Model-Predictive Control Strategies for Aircraft Deep-stall Recovery with Stability Guarantees. CDC 2019, 58th Conference on Decision and Control, Dec 2019, Nice, France. pp.ISBN: 978-1-7281-1397-5, ⟨10.1109/CDC40024.2019.9030207⟩. ⟨hal-02390139⟩