Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

This paper presents a novel flight safety assessment and management augmentation to the flight management system designed to assist a flight crew in avoiding or recovering from impending loss-of-control situations. Nominally, this system serves as a passive monitor but, in high-risk situations, warnings and (ultimately) override actions are initiated to mitigate the high-risk situation. In this work, flight safety assessment and management is applied to the task of preserving safety during takeoff, which is one of the highest-risk phases of flight. Flight safety assessment and management is specified as a deterministic Moore machine that can ultimately be certified using existing software certification processes. To facilitate understanding and to reduce state-space complexity, flight safety assessment and management’s state machines are split into longitudinal and lateral-directional submachines that identify and mitigate loss-of-control contributing factors associated with aircraft dynamics and control ...

[1]  Thomas P. Ratvasky,et al.  Envelope Protection for In-Flight Ice Contamination , 2009 .

[2]  Lynne Martin,et al.  Piloted Simulator Evaluation of Maneuvering Envelope Information for Flight Crew Awareness , 2015 .

[3]  Toshiyuki Inagaki Situation-Adaptive Autonomy: Dynamic Trading of Authority between Human and Automation , 2000 .

[4]  Eugene A. Morelli,et al.  A Generic Nonlinear Aerodynamic Model for Aircraft , 2014 .

[5]  Hans B. Pacejka,et al.  Tire and Vehicle Dynamics , 1982 .

[6]  Jo Yung Wong,et al.  Theory of ground vehicles , 1978 .

[7]  Ella M. Atkins,et al.  An evaluation of flight safety assessment and management to avoid loss of control during takeoff , 2014 .

[8]  Pascal Traverse,et al.  AIRBUS A320/A330/A340 electrical flight controls - A family of fault-tolerant systems , 1993, FTCS-23 The Twenty-Third International Symposium on Fault-Tolerant Computing.

[9]  David Zammit-Mangion,et al.  Simplified Algorithm to Model Aircraft Acceleration During Takeoff , 2008 .

[10]  Frank L. Lewis,et al.  Aircraft Control and Simulation , 1992 .

[11]  Max Mulder,et al.  Design and Evaluation of a Safety Augmentation System for Aircraft , 2014 .

[12]  R. Khatwa,et al.  A comparative evaluation of three take-off performance monitor display types , 1993 .

[13]  John E. Savage,et al.  Models of computation - exploring the power of computing , 1998 .

[14]  Nancy A. Lynch,et al.  On the formal verification of the TCAS conflict resolution algorithms , 1997, Proceedings of the 36th IEEE Conference on Decision and Control.

[15]  Domenico Pascarella,et al.  Formal Methods in Avionic Software Certification: The DO-178C Perspective , 2012, ISoLA.

[16]  Ilya Kolmanovsky,et al.  Integrator resetting for enforcing constraints in aircraft flight control systems , 2015 .

[17]  John Kaneshige,et al.  Safe Maneuvering Envelope Estimation Based on a Physical Approach , 2013 .

[18]  Makoto Itoh,et al.  Situation-adaptive autonomy: the potential for improving takeoff safety , 1997, Proceedings 6th IEEE International Workshop on Robot and Human Communication. RO-MAN'97 SENDAI.

[19]  Brent W. York,et al.  A Physically Representative Aircraft Landing Gear Model for Real-Time Simulation. , 1996 .

[20]  Marco Caccamo,et al.  Sandboxing Controllers for Cyber-Physical Systems , 2011, 2011 IEEE/ACM Second International Conference on Cyber-Physical Systems.

[21]  Ella M. Atkins,et al.  Flight safety assessment and management during takeoff , 2013 .

[22]  Carlos Canudas-de-Wit,et al.  Dynamic Friction Models for Road/Tire Longitudinal Interaction , 2003 .

[23]  Edward F. Moore,et al.  Gedanken-Experiments on Sequential Machines , 1956 .

[24]  C. C. de Visser,et al.  Optimal Control Framework for Estimating Autopilot Safety Margins , 2015 .

[25]  Ella M. Atkins,et al.  Trim State Discovery with Physical Constraints , 2015 .

[26]  John Kaneshige,et al.  An Adaptive Nonlinear Aircraft Maneuvering Envelope Estimation Approach for Online Applications , 2014 .

[27]  Ilya Kolmanovsky,et al.  Recoverable sets of initial conditions and their use for aircraft flight planning after a loss of control event , 2014 .

[28]  Klaus H. Well,et al.  Aircraft Control Laws for Envelope Protection , 2006 .

[29]  C. Edward Lan,et al.  Airplane Aerodynamics and Performance , 2016 .

[30]  Dennis S. Bernstein,et al.  Retrospective cost model refinement for aircraft fault signature detection , 2014, 2014 American Control Conference.

[31]  Gregg Bartley Boeing B-777: Fly-By-Wire Flight Controls , 2006 .

[32]  Christine M. Belcastro,et al.  Preliminary Analysis of Aircraft Loss of Control Accidents: Worst Case Precursor Combinations and Temporal Sequencing , 2014 .

[33]  Christel Baier,et al.  Principles of model checking , 2008 .

[34]  David R. Downing,et al.  Development of a takeoff performance monitoring system , 1987 .

[35]  James Rankin,et al.  Bifurcation Analysis of Nonlinear Ground Handling of Aircraft , 2010 .

[36]  Christine M. Belcastro,et al.  Future Integrated Systems Concept for Preventing Aircraft Loss-of-Control Accidents , 2010 .

[37]  M. W. Milligan,et al.  Monitoring airplane takeoff performance - Prototype instrument with learning capability , 1994 .

[38]  Christine M. Belcastro,et al.  Aircraft Loss-of-Control Accident Analysis , 2010 .

[39]  Jeffrey D. Ullman,et al.  Introduction to Automata Theory, Languages and Computation , 1979 .

[40]  C. Canudas-de-Wit Dynamic Friction Models for Longitudinal Road/Tire Interaction: Theoretical Advances , 2004 .

[41]  Ella M. Atkins,et al.  Verification Guided Refinement of Flight Safety Assessment and Management System for Takeoff , 2016, J. Aerosp. Inf. Syst..