A method of modeling for nonlinear process dynamics by chaotic time-series analysis

A method of modeling for nonlinear process dynamics by chaotic time-series analysis has been developed. It involves the search of simular characteristic short-term dynamics of the past time-series data which is compared with the present short-term time-series data using the chaotic time-series analysis and the determination of future dynamics by the past simular short-term dynamics. It was applied to the bottom temperature control loop of a demethanizer distillution column in an ethylene plant to confirm the design philosophy. The actual result indicates that the proposed method in this study has the advantage of modeling for nonlinear process dynamics.