Name
Title | ||
|---|---|---|
Analysis of model orders in human dynamics identification using linear polynomial and Hammerstein-Wiener structures |
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. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICNSC.2010.5461586 | Networking, Sensing and Control |
Keywords | Field | DocType |
autoregressive processes,polynomial approximation,production management,ARMAX model,ARX model,Hammerstein-Wiener structures,human dynamics identification,linear polynomial,model orders analysis | Production manager,Data modeling,Control theory,Human operator,Intelligent decision support system,Polynomial,Computer science,Control theory,Intelligent robots,Human dynamics,Control engineering | Conference |
ISBN | Citations | PageRank |
978-1-4244-6450-0 | 0 | 0.34 |
References | Authors | |
6 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kalevi Tervo | 1 | 0 | 0.34 |
| Aino Manninen | 2 | 0 | 0.68 |