Sae ieee aerospace control and guidance systems committee
Download
1 / 21

SAE/IEEE Aerospace Control and Guidance Systems Committee - PowerPoint PPT Presentation


  • 86 Views
  • Uploaded on

SAE/IEEE Aerospace Control and Guidance Systems Committee. Meeting 102 Grand Island, New York Oct. 15 – 17, 2008 Ron Hess Dept. of Mechanical and Aeronautical Engineering University of California Davis, CA. Outline. University of California Davis Aero Program

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' SAE/IEEE Aerospace Control and Guidance Systems Committee' - uriel-patton


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
Sae ieee aerospace control and guidance systems committee

SAE/IEEE Aerospace Control and Guidance Systems Committee

Meeting 102

Grand Island, New York

Oct. 15 – 17, 2008

Ron Hess

Dept. of Mechanical and Aeronautical Engineering

University of California

Davis, CA


Outline
Outline

  • University of California Davis Aero Program

  • Analytical Approach to Assessing Flight Simulator Fidelity

  • Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics

  • Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

Sponsor: NASA Subsonic Rotary Wing Project;

Technical Manager: Dr. Barbara Sweet


Ucd aero program 25 year celebration
UCD Aero Program25 Year Celebration

  • UC Davis Aeronautical Science and Engineering Program Celebrating 25 years since initial accreditation by ABET

  • First accredited Aeronautical/Aerospace Program in the Nine Campus UC System

    UC Davis Aero Faculty

    Jean Jacques Chattot (Dept. Chair) Valeria LaSaponara

    Roger Davis Nesrin Sarigul-Klijn

    Mohamed Hafez Bruce White (new Dean of Eng.)

    Ron Hess Case van Dam

    Sanjay Joshi


Robert mondavi food and wine institute university of california davis
Robert Mondavi Food and Wine InstituteUniversity of CaliforniaDavis


Robert mondavi center for performing arts university of california davis
Robert Mondavi Center for Performing ArtsUniversity of CaliforniaDavis


Analytical assessment of flight simulator fidelity
Analytical Assessment of Flight Simulator Fidelity

  • Pilot Model Developed That Includes

    • Visual feedback with degraded cues - Proprioceptive feedback

    • Vestibular feedback - Task interference

    • Variable skill levels

  • Aimed Toward Assessing Training Simulator Fidelity

    “We suggest, then, that fidelity is the specific quality of a simulator that permits the skilled pilot to perform a given task in the same way that it is performed in the actual aircraft. Execution …is simply the closure of all loops made necessary by both the task requirements and the dynamics of the vehicle and subject to the information available.”

    - Heffley, R. K., et al, “Determination of Motion and Visual System Requirements for Flight Training Simulators,” U.S. Army Research

    for the Behavioral and Social Sciences, TR 546, Aug. 1981.


Fidelity example small rotorcraft bo 105
Fidelity Example: Small Rotorcraft – BO-105

  • Task: Reposition task (4 control axes) with atmospheric turbulence

  • Flight Condition: near hover

  • Simulator “limitations” – 4 scenarios

  • - no motion

  • - limited motion

  • - limited motion + reduced visual cue quality

  • - limited motion + reduced visual cue quality + time delay in sim


Fidelity example small rotorcraft bo 1051
Fidelity Example: Small Rotorcraft – BO-105

pilot model for longitudinal control loops

pilot/vehicle computer simulation model

power in proprioceptive feedback signal


Fidelity example small rotorcraft bo 105 fidelity metrics larger values imply poorer fidelity
Fidelity Example: Small Rotorcraft – BO-105Fidelity Metrics(larger values imply poorer fidelity)

  • no-motion

    FM = pitch + roll + vertical position + heading

    = 1.36 + 2.39 + 0.36 + 0.837 = 4.95

  • limited-motion

    FM = pitch + roll + vertical position + heading

    = 0.4 + 0.7 +.05 + 0.15 =1.3

  • limited-motion + reduced visual quality

    FM = pitch + roll + vertical position + heading

    = 0.89 + 1.28 + 0.22 + 0.62 = 3.01

  • limited-motion + reduced visual quality + time delay

    FM = pitch + roll + vertical position + heading

    = 0.98 + 2.04 + 0.208 + 0.07 = 3.3


Fidelity Example: Large Rotorcraft – CH-53D

power in proprioceptive feedback signal

Fidelity metric calculation is independent of time-variant task demands

FM = pitch-loop contribution + roll-loop contribution + vertical velocity- loop contribution + heading-rate loop contribution

= 0.0148 + 0.02 + 0.107 + 0.0218 = 0.164

accel/decel task – time varying pilot model

hover - 110 kts - hover


Modeling pilot adaptation to sudden changes in vehicle dynamics
Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics

Adaptive Pilot Model – Single Axis Tasks

  • Four criteria for model adaptation

  • signals must be easily sensed by pilot

  • adaptation completed in 5 sec or less

  • logic in adaptation must be predicated upon information available to pilot

  • post-adapted pilot models must follow dictates of crossover model of human


Modeling pilot adaptation to sudden changes in vehicle dynamics single axis task
Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics(single-axis task)

Pilot model adapting to suddenly changing vehicle dynamics

with pulsive commands C(t)


Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics(multi-axis task with control cross-coupling)


Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics(multi-axis task with control cross-coupling)

Pilot model adapting to suddenly changing vehicle dynamics

with random-appearing commands C(t)


Modeling human pilot controlling rotorcraft with time varying dynamics
Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

Pilot Model

with Ypf

configured properly


Modeling human pilot controlling rotorcraft with time varying dynamics1
Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

From Yc = 1/s to Yc = 25/(s2+6s +25)

cue to pilot that dynamics have changed


Modeling human pilot controlling rotorcraft with time varying dynamics2
Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

High –fidelity model of Army RASCAL

Pilot model/vehicle open-loop

transfer function

Pilot/vehicle open-loop transfer function

from laboratory tracking task


Modeling human pilot controlling rotorcraft with time varying dynamics3
Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

pitch and roll SCASs changing from RC/ATTH to ATTC/ATTH over 10 sec with time-varying pilot model

cue to pilot that SCAS is changing

pilot/vehicle tracking performance

with time-varying pilot model


Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

Predicting Handling Qualities Levels

Laboratory tracking tasks

UH-60 hover task – ATTC/ATTH

SCAS


California innovation center
California Innovation Center

  • The California Innovation Center provides a mechanism where industry and universities (UCD & CSU Sacramento) will come together to support the existing technology-focused missions at Beale Air Force Base. These collaborative efforts will support additional emerging technologies that will influence and embrace the future growth of autonomous and cyber systems.


California innovation center1

Safety & Reliability Issues

Navigation

Aircraft Airworthiness

FAA Airspace Classifications

Collision Avoidance with cooperative & non-cooperative aircraft

Weather Avoidance?

Compliance with 14 CFR 91.113

Interoperability with manned / unmanned aircraft

ATC Communications

Command & Control Link

Take-off & Landing

Operator Qualifications

California Innovation Center

FAR 91.113b

When weather conditions permit, regardless of whether an operation is conducted under instrument flight rules or visual flight rules, vigilance shall be maintained by each person operating an aircraft so as to see and avoid other aircraft.


ad