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

Torbjørn Cunis1, Dominic Liao-mcpherson2, Jean-Philippe Condomines3, Laurent Burlion, Ilya V. Kolmanovsky4

  • 1ONERA -- The French Aerospace Lab
  • 2The University of Michigan
  • 3ENAC University
  • 4University of Michigan

Details

10:40 - 11:00 | Wed 11 Dec | Méditerranée C4 | WeA05.3

Session: Control of Systems Subject to Constraints

Abstract

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.