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New Types of Target Inputs for Multi-Modal Pilot Model Identification


Pool,  DM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Zaal, P., Pool, D., Mulder, M., & van Paassen, M. (2008). New Types of Target Inputs for Multi-Modal Pilot Model Identification. In AIAA Modeling and Simulation Technologies Conference 2008 (pp. 1591-1607). Red Hook, NY, USA: Curran.

Multi-modal pilot model identification can give useful insight into pilots?use of visual and physical motion cues in manual control tasks. Current pilot model estimation techniques are unable to provide reliable multi-modal pilot models for all types of control tasks. Specifically for disturbance-rejection tasks, in which the pilot visual and physical motion perceptual processes work in parallel ?i.e., have the same input signal ?current pilot model identification techniques are unable to reliably separate both responses. Therefore identifiability of multi-modal control behavior puts requirements on the design of the control task. To allow for pilot model identification from measurement data, an extra target signal needs to be ed into the closed-loop system in addition to the disturbance signal. In most previous research, a signal comparable to the disturbance, i.e., a quasi-random signal, was used for this additional target. New identification techniques allow for the use of different types of target signals, such as signals consisting of two or more discrete step-like or gradual ramp-like changes in the reference value. In this paper, the effect of these new types of target signals on pilot tracking performance and control behavior is investigated using a simulator experiment. Ramp target signals were found to be the best native to multi-sine signals for evaluating multi-modal pilot control behavior.