Measurement of Chaotic Behavior of Operator Stabilizing an Inverted Pendulum and Its Fuzzy Identification from Time Series Data
Department of Mechanical Engineering, Saitama Institute of Technology, Fusaiji 1690, Okabe, Saitama 3690293, Japan
This paper investigates the identification of the chaotic characteristics of human operation with individual difference and the skill difference from the experimental time series data by utilizing fuzzy inference. It shows 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 data. The characteristics of each operator trial were identified fairly well from experimental time series data by utilizing fuzzy reasoning. It was shown that the estimated maximum Lyapunov exponents of simulated time series data using an identified fuzzy controller were positive against embedding dimensions, which means a chaotic phenomenon. It was also recognized that the simulated human behavior have a large amount of disorder according to the result of estimated entropy from the simulated time, series data.
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