AME 555 Introduction to System Identification Methods

This course provides an introduction to the field of system identification, which involves the use data from experiments to obtain static and dynamic models useful for simulation, prediction, and control design. Topics include identification of non-parametric models including empirical transfer function and impulse response identification, as well as parametric model identification through predictor error methods. Discussion on selection of proper input data and model validation is also included. The courses makes significant use of MATLAB's System Identification Toolbox.