A physically representative aircraft landing gear model for real-time simulation

York, Brent; Alaverdi, Omeed

doi:10.2514/6.1996-3506

Cited by 7 publications

(5 citation statements)

References 1 publication

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“…I xx , I yy , I zz , and I xz are the moments of inertia of the aircraft; I w is the moment of inertia of the wheel; R wheel is the radius of the wheel; and τ brake is the braking torque produced on the wheels due to the application of brakes. Equations (A18-A20) model the effect of differential braking during the ground roll [43].…”

Section: Appendix A: Takeoff Dynamicsmentioning

confidence: 99%

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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: Appendix A: Takeoff Dynamicsmentioning

confidence: 99%

“…Modeling ground roll dynamics of the aircraft requires the knowledge of the reaction forces and moments exerted by the ground on the airframe [43], as well as aerodynamic forces that become significant as airspeed progressively increases during the takeoff roll.…”

Section: Appendix A: Takeoff Dynamicsmentioning

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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“…In this section, the mathematical model of the UCAV during takeoff roll is developed. During takeoff roll, the ground exerts forces on the landing gears of the UCAV, thus the model of the landing gears and the forces exerted by the ground will be emphasized (York and Alaverdi, 1996).…”

Section: Model Developmentmentioning

confidence: 99%

A directional control system for UCAV automatic takeoff roll

Zhang

Duan²

2013

Aircraft Engineering and Aerospace Technology

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Purpose -The purpose of this paper is to develop a directional and roll control system for unmanned combat air vehicle (UCAV) automatic takeoff roll, with the objective of keeping the UCAV along the runway centerline and keeping the wings level, especially when there is a crosswind. Design/methodology/approach -The nonlinear model of the UCAV during takeoff roll is established. The model is linearized about the lateraldirectional equilibrium point at different forward speeds. The approximate directional model and roll model are extracted using time-scale decomposition technique. Then the directional control law and roll control law are developed using gain scheduling approach. Nose wheel steering, differential brake and rudder are used as the primary directional control device at low, medium and high speeds, respectively, according to both the qualitative and quantitative analysis of their control effectiveness at different speeds. A priority matrix is developed to determine the secondary control device which is used if the primary control device fails, thus the directional control system can have a certain degree of fault tolerance. Findings -This work developed the directional control law and roll control law by using gain scheduling approach. Experimental results verified that the developed directional and roll control system has high robustness and satisfactory fault tolerance: it can guarantee a safe takeoff under a 50 ft/sec crosswind, even if one directional control device fails, which satisfies the relevant criteria in MIL-HDBK-1797. Practical implications -The directional and roll control system developed can be easily applied to practice and can steer the UCAV during takeoff roll safely, which will considerably increase the autonomy of the UCAV. Originality/value -The paper shows how time-scale decomposition technique is employed to extract the approximate directional model and roll model, which simplifies model analysis and control law design. A fault-tolerant directional control system is designed to improve safety during takeoff.

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“…The values or safety boundaries of some landing parameters are suggested under simplified conditions by Chen and Ang (2011), Chen et al (2011b), Wang (2007) and Xu et al (2011). Moreover, studies by Jiao et al (2011), Shi (2009), York and Alaverdit (1996) and Zhang et al (2009a) have developed simplified local models to simulate landing process and study landing safety.…”

Section: Introductionmentioning

confidence: 98%

Hybrid safety analysis method based on SVM and RST: An application to carrier landing of aircraft

et al. 2015

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A physically representative aircraft landing gear model for real-time simulation

Cited by 7 publications

References 1 publication

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

Flight Safety Assessment and Management for Takeoff Using Deterministic Moore Machines

A directional control system for UCAV automatic takeoff roll

Hybrid safety analysis method based on SVM and RST: An application to carrier landing of aircraft

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