An Investigation of Determinism and Chaotic Behavior in Flight Performance Data: A Chaos Theory and Nonlinear Time Series Analysis Approach

Human flight performance data were investigated using non-linear time series analysis methods to determine deterministic chaotic behavior in the data. Using a sequence of steps of non-linear methods, four flight performance data were used to investigate for the existence of deterministic chaotic behavior. Results revealed that flight performance data may exhibit chaotic behavior. Results also showed a consistent low determinism value in all the data examined which is the defining characteristic of chaotic behavior. It was also found that the data originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value which indicate chaotic behavior exist in the data revealed that most of the data examined possessed some traces of deterministic chaotic behavior evident by the low Maximal Lyapunov Exponent value

Investigation of chaotic behavior in flight airspeed error performance data.

Human pilot flight performance data was investigated using nonlinear time series analysis methods to determine deterministic chaotic behavior possessed in the data. Using a sequence of steps of nonlinear methods, flight performance data set was chosen for this study. Results revealed that flight performance data exhibit chaotic behavior with low determinism value. It was also found that data was originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value further revealed that most of the data examined possessed traces of deterministic chaotic behavior. These findings were discussed and the implication of the findings were given for the future analysis of these kind of data