This textbook presents the theoretical foundation for the System Identification Toolbox. It gives the reader an understanding of available system identification methods and their rationales, properties, and uses. This second edition introduces subspace methods, methods that utilize frequency-domain data, and general, nonlinear, black box methods including neural networks and neuro-fuzzy modeling. The book contains many new computer-based examples, which utilize the System Identification Toolbox, a MATLAB application toolbox developed by Lennart Ljung. The toolbox may be purchased from The MathWorks.
Companion Software: A set of MATLAB M-files is available.
Teaching materials based on MATLAB and Simulink