Reconfigurable Fault-Tolerant Predictive Flight Control
Currently, commercial aircraft fault tolerant control (FTC) strategies in the flight control system (FCS) are based on fail-safe approaches whereby a nominal ("normal") control law is switched first to a robust ("alternate") solution and then if necessary to a "direct" law. Note that despite its name, the later law ensures a minimal level of stability augmentation independently of the type of abnormal event. The advantages of the current approach are the ease of design, analysis and certification.
Each control law is designed off-line for different levels of robustness and each includes a set of specific guidance and control (G&C) functions which assist the pilot during the flight. Some of these functions are switched off as the control law is switched from "normal" to "direct" and even though this state-of-practice is safe, it is also known to decrease the easiness of the piloting task and as functions get de-activated the use of automatic guidance (Auto-Pilot) or navigation systems (Flight Management) is prevented.
More advanced and less conservative FTC-FCS approaches have not been used due to mainly:
- A lack of demonstrated maturity of reconfigurable G&C methods for aircraft.
- A lack of research in the practical limitations arising from the interaction of reconfigurable G&C systems with the estimation and diagnostic systems that feed the first with the required information to reconfigure or adapt their behaviour.
- A definite gap in terms of the clearance problem, which is a precursor for FCS certification, for this type of G&C systems.
The previous standard FTC-FCS approach was programmatically pursued since aircraft makers seek above all safety and acceptable performance (Robust Stability). But for the future aircraft, it has been identified the need to change the design paradigm towards a performance-oriented one:
"Full-time & all-event availability of performance-optimized G&C functions"
This paradigm can be translated into the desire to extend the operability of the G&C functions designed to assist the pilot in keeping the flight safe and making the flight task easier and the mission optimal.
Project team members
- Laura Ferranti
- dr. Yiming Wan
- dr.ir. Tamas Keviczky
Reconfigurable control, fault-tolerant control, predictive control, operator splitting, first-order optimization methods, embedded optimization-based control, fault detection and reconfiguration, moving horizon estimation, active diagnosis, real-time computation, flight control.
EU FP7/2007-2013 under grant agreement n. AAT-2012-RTD-2314544 Reconfiguration of Control in Flight for Integral Global Upset Recovery (RECONFIGURE)
Deimos Space S.L.U., Airbus Operations SAS, DLR, ONERA, SZTAKI, University of Exeter, University of Cambridge, University of Bristol
The main goal of RECONFIGURE is to investigate and develop aircraft guidance and control (G&C) technologies that facilitate the automated handling of off-nominal/abnormal events (such as unusual attitude and aerodynamic angles, faulty actuators and sensors, wing-icing, etc.) and optimize the aircraft status and flight. The automatism of the G&C will help alleviate the pilots' task and optimize performance by automatically reconfiguring the aircraft to its optimal flight condition. This automatism and optimization must be performed while maintaining the current aircraft safety levels.
In particular, we investigate on-line predictive control based approaches to integrated fault-detection and isolation, along with inexact optimization methods that allow the predictive controllers to be implemented and certified in embedded real-time control environments, and undergo industrial verification and validation for flight clearance analysis. In addition, we also develop data-driven moving horizon robust fault estimation methods using online optimization to support reconfigurable control strategies. The developed methods are tested on a high fidelity industrial aircraft simulator, and undergo industrial validation at Airbus facilities.
For more information, please visit the RECONFIGURE project website at http://reconfigure.deimos-space.com/.
- Online Optimization-Based Predictive Flight Control Using First-Order Methods, PhD Thesis Ferranti, L., 2017-09-06
- Operator-Splitting and Gradient Methods for Real-Time Predictive Flight Control Design, L. Ferranti and T. Keviczky, Special Issue on ``Computational Guidance and Control'' in the AIAA Journal of Guidance, Control, and Dynamics, Vol. 40, No. 2, February 2017, pp. 265-277.
- Data-Driven Robust Receding Horizon Fault Estimation, Y. Wan, T. Keviczky, M. Verhaegen and F. Gustafsson, Automatica, September 2016, Vol. 71, No. 9, pp. 210-221.
- An adaptive constraint tightening approach to linear model predictive control based on approximation algorithms for optimization, I. Necoara, L. Ferranti and T. Keviczky, Special Issue on “Predictive Control for Embedded Systems” in Optimal Control Applications and Methods, Wiley InterScience, Vol. 36, No. 5, September/October 2015, pp. 648-666.