Identifying Human Control Behavior

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Transcription:

Identifying Human Control Behavior In the SIMONA Research Simulator Dr. ir. Herman Damveld 2-6-2010 Challenge the future

Outline Aerospace Engineering Human Control Research at Aerospace Engineering Identifying pilot control parameters using visual, vestibular and haptic cues. 1. Experimental Behavior Measurement Method: Aircraft Handling Qualities 2. VIDI: Simulator Fidelity 3. Boeing: Measuring Neuromuscular System Contribution Identifying Human Control Behavior 2 25

Aerospace Engineering Control & Simulation Division Staff: 2 full professor (Max Mulder, Bob Mulder) 2 associate professors Scientific, technical & support staff 25 PhD students 25-35 MSc students annually Research areas: Human-machine systems and flight simulation Guidance and control of aircraft and rotorcraft Flight deck avionics and air traffic management Dynamics and control of spacecraft Identifying Human Control Behavior 3 25

Facilities Human-Machine Systems Lab Cessna Citation II SIMONA Research Simulator Identifying Human Control Behavior 4 25

Case 1: Experimental Behavior Measurement Method Identifying Human Control Behavior 5 25

Experimental Behavior Measurement Method Aircraft Handling Qualities Current status: Pilot evaluation Phase 1: Familiarization Phase 2: Full envelope evaluation Phase 3: Operational task evaluation How can we measure handling qualities -objectively - over full handling qualities envelope Identifying Human Control Behavior 6 25

Experimental Behavior Measurement Method Displays Pilot Inceptor Vehicle Dynamics - By measuring the pilot control behavior conclusions can be drawn about the handling qualities of the aircraft. The forcing function on the head-up display forces the pilot to adopt a highfrequency control strategy. Identifying Human Control Behavior 7 25

Experimental Behavior Measurement Method Identifying Human Control Behavior 8 25

Experimental Behavior Measurement Method Identifying Human Control Behavior 9 25

Experimental Behavior Measurement Method Results Crossover-regression frequency is a measure for handling qualities Identifying Human Control Behavior 10 25

Case 2: VIDI Project / Simulator Fidelity Identifying Human Control Behavior 11 25

VIDI: Simulator Fidelity 1 multi-loop pilot models & identification techniques 2 identify pilot model in real flight δ 3 identify pilot model in the simulator 4 improve the simulator motion cueing 5 framework for human-centered fidelity metric Identifying Human Control Behavior 12 25

VIDI: Simulator Fidelity Displays Pilot Inceptor Vehicle Dynamics - Identifying Human Control Behavior 13 25

VIDI: Simulator Fidelity Displays Sensors Equalization Neuromuscular System Inceptor Vehicle Dynamics - A second forcing function perturbs the elevator of the aircraft and is needed to identify the contributions of the visual and vestibular systems separately. Identifying Human Control Behavior 14 25

VIDI: Simulator Fidelity Displays Sensors Equalization Neuromuscular System Inceptor Vehicle Dynamics - The pilot is described by 8 parameters which we can determine using system identification techniques. Identifying Human Control Behavior 15 25

VIDI: Simulator Fidelity Results visual model parameters vestibular model parameters 1.0 K v T L τ v K m τ m 3.0 0.40 6 0.40 0.8 2.5 0.35 5 0.35 0.6 0.4 2.0 1.5 1.0 0.30 0.25 0.20 4 3 2 0.30 0.25 0.20 0.2 0.5 0.15 1 0.15 0.0 C CM 0.0 C CM 0.10 C CM 0 C CM 0.10 C CM Identifying Human Control Behavior 16 25

Case 3: Boeing Balked Landing Study Identifying Human Control Behavior 17 25

Boeing: Measuring the NMS Contribution Balked Landing Study Goal: Improve the model of the neuromuscular system and estimate its parameters Identifying Human Control Behavior 18 25

Boeing: Measuring the NMS Contribution Displays Sensors Equalization Neuromuscular System Vehicle + Inceptor Dynamics - A third forcing function adds force perturbations to the control inceptor and is required to identify the admittance of the spinal neuromuskuloskeletal dynamics as well as the combined physical interaction. This allows us to subdivide the McRuer NMS in a feedback part (combined physical interaction) and an equalization part. Identifying Human Control Behavior 19 25

Boeing: Measuring the NMS Contribution Control inceptor Fcontact u (displ) Spinal nms Hgto Hcontact - Eff m.c. - - A Hact - Hlimb u limb Htendon u tendon - Hintrin Hms Identifying Human Control Behavior 20 25

Boeing: Measuring the NMS Contribution Admittance Identifying Human Control Behavior 21 25

Boeing: Measuring the NMS Contribution Validation: Electromyographic Measurements Isometric Force Measurement Identifying Human Control Behavior 22 25

Boeing: Measuring the NMS Contribution Results Visual response Vestibular response Visual Vestibular McRuer NMS Identifying Human Control Behavior 23 25

Boeing: Measuring the NMS Contribution Results Spinal NMS Combined physical interaction SNMS CPI The difference between the parameters in the McRuer NMS and the CPI is assumed to be caused by the equalization part of the NMS (current investigation). Identifying Human Control Behavior 24 25

Summary / Conclusions Present techniques allow us describe the pilot control behavior by identifying the contributions to the total pilot model of the: Visual system (4 parameters) Vestibular system (2 parameters) The McRuer neuromuscular system (2 parameters) The full spinal NMS (15 parameters) These parameters can provide information about: The vehicle handling qualities The use of modal information (visual, vestibular, haptic) The human actuator settings Identifying Human Control Behavior 25 25