ME 58400 - System Identification

Credit Hours: 3.00. Theory and application of System Identification methods. Connecting the world of mathematical models to experimental data - least squares methods and difference equation models. Background in probability and analysis: algebra of random variables, law of large numbers, central limit theorem. The ARMA family of models; mapping physics models to generalized ARMAX forms (linear and nonlinear); mapping the parameter estimation problem to the least squares problem (batch and recursive), and numerical solution techniques. Model (in)validation, optimal identification criteria, experiment design and data preprocessing considerations. Issues of signal-to-noise ratio, persistency of excitation, sampling frequency, data accuracy and data sizes. Credits: 3.00

Communication

Campus

Services

Other

ME 58400 - System Identification