SAE/IEEE Aerospace Control and Guidance Systems Committee

Meeting 102Grand Island, New York

Oct. 15 – 17, 2008

Ron HessDept. of Mechanical and Aeronautical Engineering

University of CaliforniaDavis, CA

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 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 LaSaponaraRoger Davis Nesrin Sarigul-KlijnMohamed Hafez Bruce White (new Dean of Eng.)

Ron Hess Case van DamSanjay Joshi

Robert Mondavi Food and Wine InstituteUniversity of California

Davis

Robert Mondavi Center for Performing ArtsUniversity of California

Davis

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

• 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-105

pilot/vehicle computer simulation model

pilot model for longitudinal control loops

power in proprioceptive feedback signal

• 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: Small Rotorcraft – BO-105Fidelity Metrics

(larger values imply poorer fidelity)

Fidelity Example: Large Rotorcraft – CH-53D

accel/decel task – time varying pilot model hover - 110 kts - hover

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

Fidelity metric calculation is independent of time-variant task demands

power in proprioceptive feedback signal

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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)

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)

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Modeling Pilot Adaptation to Sudden Changes in Vehicle Dynamics

(multi-axis task with control cross-coupling)

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Pilot model adapting to suddenly changing vehicle dynamics with random-appearing commands C(t)

Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

Pilot Model

MUM

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configured properly

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 Dynamics

High –fidelity model of Army RASCAL

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Pilot/vehicle open-loop transfer function from laboratory tracking task

Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

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violation of normaloperating area

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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

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Level 1

Modeling Human Pilot Controlling Rotorcraft with Time-Varying Dynamics

Predicting Handling Qualities Levels

Laboratory tracking tasks UH-60 hover task – ATTC/ATTHSCAS

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.

Collision Avoidance with cooperative & non-cooperative aircraft

Interoperability with manned / unmanned

aircraftATC

Communications

Compliance with 14 CFR 91.113

Take-off & Landing

FAA Airspace

Classifications

Weather Avoidance?

Safety & Reliability Issues Navigation

Command & Control Link

Operator Qualifications

Aircraft Airworthiness

FAR 91.113bWhen 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.

California Innovation Center