Optimal Control Framework for Estimating Autopilot Safety Margins

Govindarajan, Nithin; Visser, Coen C. de; Kampen, E. van; Krishnakumar, Kalmanje; Barlow, Jonathan; Stepanyan, Vahram

doi:10.2514/1.g000271

Cited by 16 publications

(14 citation statements)

References 27 publications

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“…For example, Govindarajan et al [22] proposed an optimal control framework to analyze flight control laws and estimate constraints on the reference commands. These constraints were then used by the autopilot to ensure that the aircraft stayed within safe operating envelopes.…”

Section: A Flight Safety Architecturesmentioning

confidence: 99%

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Balachandran

Atkins

2015

Journal of Aerospace Information Systems

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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 constraints. Case studies based on documented takeoff accidents are presented to evaluate flight safety assessment and management's ability to maintain safe flight in realistic loss-of-control scenarios. Results from these case studies illustrate that flight safety assessment and management could have averted the takeoff accidents that were considered. A discussion of other factors that must be considered before realizing a comprehensive flight safety assessment and management capability for takeoff is provided. NomenclatureA lg = longitudinal takeoff logic A lt = lateral takeoff logic ap = envelope aware autopilot control C L , C D = lift and drag coefficients h = altitude p, q, r = angular rates p = pilot control T, W = thrust and weight u, v, w = velocities in the body frame V = true airspeed V lof = liftoff speed V R = takeoff rotation speed V 1 = takeoff decision speed X = longitudinal position on runway Y = lateral position on runway y = crosstrack error α, β, γ = angle of attack, sideslip angle, and flight-path angle δ a , δ r = aileron and rudder inputs ρ, μ, S ref = atmospheric density, friction coefficient, and planform area ϕ, θ, ψ = roll, pitch, and yaw angles

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Section: A Flight Safety Architecturesmentioning

confidence: 99%

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Balachandran

Atkins

2015

Journal of Aerospace Information Systems

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“…By this definition, the safe set is a collection of states from which the trajectories are guaranteed not to leave the accepted operation envelope, which, unlike the former one, forms a safety-preserving problem. 11,18 Both the reachability analysis and viability theory provided a solid framework for control synthesis and trajectory analysis of constrained dynamical systems in a setvalue fashion. 19 The solutions to computing reachable set and viability set are basically classified into two categories: Lagrangian method and Euler method.…”

Section: 16mentioning

confidence: 99%

“…The task of envelope protection can be generally divided into two steps: one is the determination of safe flight envelopes; and the other is to guarantee that the aircraft states stay within the safe flight envelope. 10 As to the second step, there exist literatures 6,10,11 covering how to help keep aircraft flying within pre-defined state boundaries and detect potential hazards through constant health monitoring, during which warnings will be given if certain boundaries 7 are violated due to some aggressive manoeuvres like abrupt pitch down and up of high angles. The research of this paper, on the other hand, focuses on the first step, which is the prerequisite of flight envelope protection system.…”

mentioning

confidence: 99%

“…Alternatively, there are also various analytical methods to calculate the flight envelopes due to different definitions and numerical tools. 4,11,12 One important research in the area was the computation of attainable equilibrium/trim states and observing how control properties change with flight conditions and parameters via bifurcation analysis, 5, 13, 14 which has been developed to examine equilibrium structure of the aircraft at or near bifurcation points, indicating highly nonlinear upset conditions. Moreover, many nonlinear methods based on Lyapunov's stability theory have been proposed as a region of attraction (ROA) prediction tool.…”

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confidence: 99%

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Online Safe Flight Envelope Prediction for Damaged Aircraft: A Database-driven Approach

Zhang

Visser

Chu

2016

AIAA Modeling and Simulation Technologies Conference

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This paper proposed a framework of database-driven approach to solve the problem of online safe flight envelope prediction for aircraft safe recovery under abnormal conditions. On occurrence of sudden accidents like structural damages, conventional systems have neither enough measurements for the online reidentification of global damaged models, nor enough time for the onboard safe flight envelope computation. To circumvent these technical bottlenecks and make online applications more feasible in such emergency situations, some information, like global damaged models and the corresponding safe flight envelops, could be stored offline in a database for later online retrieval.

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“…6,7 In this framework the B-coefficients of a multivariate simplex spline are defined using a univariate spline function of a different variable. This framework was used by Govindarajan et alto estimate autopilot safety margins, 7 and by Sun et alin an aircraft system identification framework.…”

Section: Introductionmentioning

confidence: 99%

Quadrotor System Identification Using the Multivariate Multiplex B-Spline

Visser

Kampen

2015

AIAA Atmospheric Flight Mechanics Conference

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A novel method for aircraft system identification is presented that is based on a new multivariate spline type; the multivariate multiplex B-spline. The multivariate multiplex B-spline is a generalization of the recently introduced tensor-simplex B-spline. Multivariate multiplex splines obtain similar or better approximation accuracy using less parameters (B-coefficients) than standard multivariate simplex B-splines which are currently used for aircraft system identification. The multiplex spline allows the user to incorporate a-priori knowledge of the modelled system in the definition of the model structure. In particular, while the standard simplex B-splines use a multi-dimensional triangulation in which all dimensions are coupled, the multiplex spline enables the user to decouple specific model dimensions based on expert knowledge of the system. The new method is used to approximate a 4-dimensional nonlinear quadrotor inflow dataset. The results show that the multiplex B-spline obtains a relative root mean square error of 0.672% using 1440 Bcoefficients. This compares favorably to results obtained with the standard 4-dimensional simplex B-spline on the same dataset, which resulted in an relative root mean square error of 1.608% using 1540 B-coefficients.

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Optimal Control Framework for Estimating Autopilot Safety Margins

Cited by 16 publications

References 27 publications

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Online Safe Flight Envelope Prediction for Damaged Aircraft: A Database-driven Approach

Quadrotor System Identification Using the Multivariate Multiplex B-Spline

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