Abstract:
The identification of a human operator's dynamic characteristics has been an important research subject for decades. Several solutions have been proposed to obtain the mo...Show MoreMetadata
Abstract:
The identification of a human operator's dynamic characteristics has been an important research subject for decades. Several solutions have been proposed to obtain the model of the human operator as a controller but usually the methods require separate tests to record suitable data for identification. That is, the models cannot be estimated during normal work. This paper focuses on identification of a linear or quasilinear human operator model based on normal task execution data. The performances of ARX, ARMAX and Hammerstein-Wiener models with different orders are compared in time and frequency domains.
Date of Conference: 10-12 April 2010
Date Added to IEEE Xplore: 06 May 2010
ISBN Information: