TY - GEN
T1 - Economic Model-Predictive Control Strategies for Aircraft Deep-stall Recovery with Stability Guarantees
AU - Cunis, Torbjorn
AU - Liao-Mcpherson, Dominic
AU - Condomines, Jean Philippe
AU - Burlion, Laurent
AU - Kolmanovsky, Ilya
N1 - Funding Information:
This work was supported by Fondo de Investigaciones Sanitarias (FIS; ISCIII, Plan Nacional I+D+I 2008–2011 and 2013–2016: Refs 13/01207 , 12/02080 ) and cofinanced by FEDER funds. L. Pérez-Lago holds a contract from CIBERES (Ref CP13/27/01). Ramón y Cajal Spanish research grant RYC-2012-10627 and MINECO research grant SAF2013-43521-R (to I.C.). All authors report no conflicts of interest relevant to this article.
Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - 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.
AB - 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.
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U2 - 10.1109/CDC40024.2019.9030207
DO - 10.1109/CDC40024.2019.9030207
M3 - Conference contribution
AN - SCOPUS:85082506598
T3 - Proceedings of the IEEE Conference on Decision and Control
SP - 157
EP - 162
BT - 2019 IEEE 58th Conference on Decision and Control, CDC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 58th IEEE Conference on Decision and Control, CDC 2019
Y2 - 11 December 2019 through 13 December 2019
ER -