A Cybernetic Approach to Asses Simulator Fidelity
Today, the aviation community relies heavily on the use of flight simulators as they provide an efficient and cost-effective platform for research and pilot training. Currently the fidelity of a simulator is generally determined by the capabilities of its hardware, such as bandwidth and time delay of the motion system. Due to technological constraints and a limited understanding of human capabilities, differences in visual and physical motion cues cause pilots to behave differently in the simulator, affecting the validity of simulator experiments and its effectiveness for training. Therefore, a better way to describe the fidelity of a simulator would be to identify to what extent a simulator induces pilot control behavior comparable to that in the real world.
The goal of this project is to develop a method to objectively and quantifiably assess the extent to which a flight simulator supports real-flight pilot control behavior and, when discrepancies occur, to trace them back to the way the multi-modal stimuli are presented in the simulator. A cybernetic approach is adopted in which pilot behavior is captured in system-theoretical models. The project aims to provide:
- new identification techniques to identify multi-modal pilot models;
- a database of behavioral models obtained in real flight, the baseline;
- a database of models obtained in the simulator, where through a systematic variation of simulator visual and motion settings the discrepancies in behavior can be determined;
- algorithms to optimize the way the multimodal stimuli are generated through minimizing behavioral discrepancies;
- a generic framework to assess fidelity from a behavioral perspective.
Modeling multi-modal perception and control
The human controller is a non-linear biological system, but when properly trained and given constant conditions, can be described by a quasi-linear time-invariant model. This means that a pilot can be modeled by linear frequency response functions and a remnant signal that accounts for non-linear behavior. In an active control task (e.g., keeping an aircraft wings level while flying in turbulent conditions), the pilot is actively controlling the aircraft and is considered to be a continuous control element operating in closed-loop. Information about the state of the aircraft is perceived using different modalities (e.g., visual and vestibular senses) and a proper control action is generated.
To properly model the pilot’suse of different modalities a frequency response function needs to be estimated for every perceived cue. Identification of the multiple response functions requires inserting as many deterministic forcing functions at different locations in the control loop, as the number of frequency response functions to be estimated.
In-flight experiments
In the first in-flight experiments a target forcing function and a disturbance forcing function will be used on the aircraft pitch attitude, resulting in a combined pitch target following disturbance rejection task. The target forcing function will be presented visually to the pilot and the disturbance forcing function will be a physical disturbance to the aircraft. This allows for the identification and modeling of the pilot’s visual and physical motion response.
The target forcing function can be introduced relatively easy via a display in the cockpit. The introduction of the disturbance forcing function is more elaborate. A fly-by-wire system will be built into the aircraft, which utilizes the existing automatic control system. The pilot will control the aircraft with a sidestick and a fly-by-wire computer will add the disturbance forcing function to the control signal of the pilot. This signal will then drive the electrical servo of the elevator, resulting in a direct disturbance of the aircraft. During the experiment the autopilot will retain control of the roll and yaw attitude of the aircraft.
Simulator experiments
After the in-flight experiments have been completed, the exact same piloting task will also be performed in the six degree-of-freedom SIMONA Research Simulator. By varying the settings of visual display generators and motion base drive algorithm settings and comparing the results with those obtained from the in-flight experiments, insight can be gained into how pilots adapt their control behavior to what simulators support. The goal of this phase of the project is to find optimal simulator settings for establishing equal control strategies in the aircraft and simulator and develop a framework for achieving behavioral fidelity in flight simulators.
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The Cessna Citation II laboratory aircraft and the SIMONA Research Simulator used for the in-flight and the simulator experiments respectively.
Sponsors
This project is funded with a NWO Vidi grant (www.nwo.nl)
Contacts
Dr. Ir. M. Mulder
Ir. P.M.T. Zaal
Ir. D.M. Pool
Publications
[1] Steurs, M., Mulder, M., and van Paassen, M. M., “A Cybernetic Approach to Assess Flight Simulator Fidelity”, Proceedings of the AIAA Modelling and Simulation Technologies Conference and Exhibit, Providence (RI), No. AIAA-2004-5442, 16–19 Aug. 2004.
[2] Nieuwenhuizen, F. M., Zaal, P. M. T., Mulder, M., and van Paassen, M. M., “A New Multi-Channel Pilot Model Identification Method for Use in Assessment of Simulator Fidelity”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Keystone (CO), No. AIAA-2006-6629, 21–24 Aug. 2006.
[3] Van den Berg, P., Zaal, P. M. T., Mulder, M., and van Paassen, M. M., “Preparation for Conducting Multi-Modal Pilot Model Identification in Real Flight”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Keystone (CO), No. AIAA-2006-6630, 21–24 Aug. 2006.
[4] Van den Berg, P., Zaal, P. M. T., Mulder, M., and van Paassen, M. M., “Conducting multi-modal pilot model identification - Results of a simulator experiment”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Hilton Head (SC), No. AIAA-2007-6892, 20–23 Aug. 2007.
[5] Pool, D. M., Mulder, M., and van Paassen, M. M., “A Review of the Hosman and Van der Vaart Tracking Experiment”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Hilton Head (SC), No. AIAA-2007-6896, 20–23 Aug. 2007.
[6] Duppen, M., Zaal, P. M. T., Mulder, M., and van Paassen, M. M., “Effects of Motion on Pilot Behavior in Target, Disturbance and Combined Tracking Tasks”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Hilton Head (SC), No. AIAA-2007-6894, 20–23 Aug. 2007.
[7] De Bruin, J., Mulder, M., van Paassen, M. M., and Zaal, P. M. T., “Pilot’s Use of Heave Cues in a Pitch Control Task”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Hilton Head (SC), No. AIAA-2007- 6895, 20–23 Aug. 2007.
[8] Zaal, P. M. T., Nieuwenhuizen, F. M., Mulder, M., and van Paassen, M. M., “Perception of Visual and Motion Cues during Control of Self-Motion in Optic Flow Environments”, Proceedings of the AIAA Modeling and Simulation Technologies Conference and Exhibit, Keystone (CO), No. AIAA-2006-6627, 21–24 Aug. 2006.
