System Identification: A Frequency Domain Approach, 2nd edition
How does one model a linear dynamic system from noisy data? This book presents a general approach to this problem, with both practical examples and theoretical discussions that give the reader a sound understanding of the subject and of the pitfalls that might occur on the road from raw data to validated model. The emphasis is on robust methods that can be used with a minimum of user interaction.
System Identification: A Frequency Domain Approach is written for practising engineers and scientists who do not want to delve into mathematical details of proofs. Also, it is written for researchers who wish to learn more about the theoretical aspects of the proofs. Several of the introductory chapters are suitable for undergraduates. Each chapter begins with an abstract and ends with excercises, and examples are given throughout.
Software support for identifying multivariable systems is freely available at the website http://booksupport.wiley.com via Matlab® m-files (design of multi-input periodic excitations, nonparametric frequency response matrix measurements using periodic and random excitations, detection and quantification of nonlinear distortions in FRM measurements, parametric transfer function modeling using nonparametric noise models, and simultaneous parametric identification of noise and plant models)