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System Identification
Credits
9hp (+3hp for an optional project).
Course description
The course covers fundamental theory and methods for identification of dynamical systems, i.e. how to use measured input-output data to build mathematical models, typically in terms of differential or difference equations.
Periodicity
Every 2 years.
Information for Fall 2020
The course will start on Wednesday October 7 at 13:15-15:00 and the whole course will be given in distance mode.
Prerequisites
Basic undergraduate courses in statistics, stochastic processes and signals and systems.
Contents
- The mathematical foundations of system identification
- Non-parametric techniques
- Parametrizations and model structures
- Parameter estimation
- Asymptotic statistical theory
- User choices
- Experimental design
- Choice of model structure
Literature
L. Ljung: System Identification: Theory for the User. Prentice Hall 1999, 2nd ed
Contact person
Informationsansvarig: Martin Enqvist
Senast uppdaterad: 2021-09-15
