CHEM ENG *762 / Time Series Analysis and Process Identification

3 unit(s)

Staff

Methods for modeling the dynamic-stochastic behaviour of a process and its disturbances using data collected from the process. Traditional methods for impulse and frequency response identification. Discrete transfer function and ARIMA time series models. Statistical methods for structure determination, parameter estimation, model validation, design of experiments, and analysis of closed-loop data. Use of models for forecasting, analysis, and control.