Abstract
In order to stabilize the inherent unstable system like the inverted pendulum on a cart, severe judgment of situation by the operator is required. Accordingly, it can be expected that the human operators exhibit a complex behavior occasionally. This paper tried to identify the chaotic characteristics of human operation from the experimental time series data by utilizing fuzzy inference. It showed how to construct rules automatically for a fuzzy controller from experimental time series data of each trial of each operator to identify a controller from human-generated decision-making. Furthermore, it tried to identify the individual difference of human operator's behavior from time series data and acquire individual skill of human operator. It also investigated the chaotic behavior of human operator and the possibility of the formation of complex system composed of the human operator and the control objects. The operators in the experiment are skilled to some extent in stabilizing the inverted pendulum by training, and the data of ten trials per person were successively taken for an analysis, where the waveforms of pendulum angle and cart displacement were recorded. The maximum Lyapunov exponents were estimated from experimental time series data against embedding dimensions. It was found that the rules identified for a fuzzy controller from time series data of each operator showed well the human -generated decision-making characteristics with the chaos and the large amount of disorder. It was also found that the individual difference of the degrees of freedom and the amount of disorder in the system composed of the human operator and the control objects.
