Development of a Pilot Model for Air-to-Surface Tracking from Flight Test Data

Transcription

1 Development of a Pilot Model for Air-to-Surface Tracking from Flight Test Data The Role of Pilot Modeling in Evaluation of Handling Qualities DGLR International Workshop November 2008, Manching, Germany Oliver Brieger, German Aerospace Center (DLR) Daniel Ossmann, German Aerospace Center (DLR) Lt Col Markus Rüdinger, WTD 61 Dr. Matthias Heller, EADS Slide 1

2 Overview Objective of Pilot Modeling Flight Test Preparation and Execution Introduction of Ground Attack Test Equipment (GRATE II) Flight Parameters and Simulated Attack Geometry Target Signal Generation Flight Test Data Analysis System Identification Pilot s Error Function Derivation of Pilot Models Discussion and Conclusion Slide 2

3 Objectives of Pilot Modeling Application in (linear) Handling Qualities Criteria Stability Analysis Early Detection of Handling Qualities Deficiencies in the FCS Design Phase Prevention/ Investigation of PIO Incidents/Accidents input visual/displayed perception perceived error disturbances Pilot pilot command Aircraft output Man-machine-control-loop Slide 3

4 Difficulties in Pilot Modeling Human pilot is a highly non-linear, adaptable control element mathematical description very difficult and predominantly limited to linear representations Commonly used pilot models in handling qualities criteria are fairly simple (e.g. pure gain, lead/lag element, time delay) and limited to specific tasks, primarily air-to-air tracking tasks/ approach and landing phase of flight Aim: Development of a flight test method which allows the derivation of linear mathematical models of the human pilot for the longitudinal and lateral-directional motion for air-to-surface tracking Slide 4

5 Ground Attack Test Equipment II (GRATE II) Based on GRATE and ATLAS systems developed in the late 80s to evaluate handling qualities during airto-surface tracking Ground Station: radio, sequence generation, transmitter Radio Aircraft Array of lighted targets are placed at predefined positions on the ground During a prolonged gun attack, target lights are illuminated in a predefined sequence Target Area Pilot has to acquire and track the respective target expeditiously and precisely, being forced to react continuously using a high gain piloting technique Sequences are adapted to excite the closed-loop pilot-aircraft system over a wide frequency range to meet system identification requirements Slide 5

6 Flight Test Parameters and Simulated Attack Geometry TSPJ AIM9L-dummy 3 NM Pull-up Point 3 empty pylons AIM9L-dummy CFD external fuel tanks Base Distance 3.74 NM Base Parameters (400 kt/ 3664 ft) Roll-In Tracking Point Slide 6

7 Target Array Geometry Requirement: nearly uniform and small angle variations (0.4-1 deg) due to small perturbations approach x x m 123 m 112 m 102 m x 2 y 4 y 1 y 2 x 3 =y 3 x 4 y 5 y Aperture Angle [deg] 1 deg limit 0.4 deg limit Last angle alteration x 5 Distance x to reference target 4 x 21.5 m Slide 7

8 Input Signal into the Pilot-Aircraft System Defined by: The varying line of sight between the aircraft and the individual targets Target illumination sequence α α 4 α α 3 2 α α 3 α α 1 x x 1 x 2 x 3 x 4 x 5 Amplitude [deg] Aperture angle progression [deg] v x4 Distance x to the reference target [m] v x1 v x3 α 1 +α 2 α 2 α 3 α 3 +α 4 Multi-step Approximation r(t) Distance x to the reference target [m] v x5 v x3 v x4 Slide 8

9 Sequence Selection Maximized power spectra over a wide frequency range Fourier Analysis R( ω) T 2 N N N t 1 = t v j + i t 1 1 cos( ω Δ ) Δ cos( ω Δ ) v j kv 2 + k ( ω Δt) N j N j k = 1 = 1 = C P Amplitude Spectrum Amplitude [deg] C 0.5 CP 0.5 P 0.5 Δt = 2.25s 3s maximum of C 0 π/2 π 3π/2 2π 0 π/2 Frequency ω [rad/s] π 3π/2 2π Frequency ω [rad/s] 1 cos( ω Δt) 2 Δt 2 ( ω Δt) ω[rad/s] zero location Δt [s] Slide 9

10 Slide 10

11 System Identification General: Known in- and output signals used to derive mathematical models Time domain system identification based on maximum likelihood estimation Air to surface tracking task: Inputs: Visual tracking errors Outputs: Pilot control inputs u u dynamic system mathematical model x(t) = f [x(t), u(t), p] z y e Θ e Ψ Mathematical description of the pilot δ x δ y δ P y(t) = g [x(t), u(t), p] Slide 11

12 Tracking Error desired line of sight (Θ des,ψ des ) heading error e Ψ y Θ and Ψ x absolute error e current line of sight elevation error e Θ Error e Θ target change Time [s] Pitch error function Slide 12

13 Determination of System-Inherent Time Delays Determination of rise and decay times affecting pilot reaction time Earlier tests have shown that pilot needs approximately 0.5 sec to become aware of new target Onset behavior: Decay behavior: Light Intensity [%] measured approximated measured approximated Time [s] Time [s] Slide 13

14 Identification Results Longitudinal Model Stick Activity δ x [rad] Tracking Error e Θ [rad] measured identified Time [s] System identification results and error function Pilot ε x _ e Θ e τs K rp K gp s δ x F stx q com aircraft dynamics Θ Longitudinal pilot model Slide 14

15 Identification Results Lateral-Directional Model Error function e Ψ [rad] Stick activity δ y [rad] measured identified Pedal δ P [rad] Lateral/directional pilot model Time [s] System identification time histories Slide 15

16 Summary & Outlook First step on the way to a more sophisticated pilot model for air-tosurface tracking Further refinement of the model to include combined axis-inputs, biomechanical aspects and switching logic to account for varying pilot control strategies GRATE II proved to be an invaluable tool to investigate pilot dynamics in a realistic, operationally relevant environment Slide 16

17 Questions? Slide 17