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Modelling and Learning for Dynamical Systems (TSRT92)
This course is focused on methods and principles for constructing mathematical models of dynamic systems, both using first principles and data-driven methods, and about how properties of the models can be studied through simulation.
Course contents
- General introduction to models and model building: Model types, dimension and scaling, model simplification
- System identification:> Estimating transient response, spectral estimation, identification of parametric models, identification of nonlinear models, validation
- Physical Modeling: Physical principles, object-oriented modeling.
- Simulations: Choice of methods, stability, accuracy.
Organisation
- Lectures: 12
- Exercises: 12 (7 in computer room)
- Labs: 3 (compulsory)
- Exam: 4-hour computer exam
Lecturer and examiner
Teaching assistants
Course material
- Textbook: L. Ljung, T. Glad and A. Hansson: Modelling and Identification of Dynamical Systems, second edition. Studentlitteratur. (2021) ISBN 9789144153452
- Exercise book:
- Swedish Edition: P. Lindskog, T. Glad, L. Ljung och J. Roll: Modellbygge och simulering. Ovningsbok. Studentlitteratur. (2nd edition, 2008)
- English edition: P. Lindskog, T. Glad, L. Ljung and J. Roll: Modeling and Identification of Dynamical Systems: Exercises Studentlitteratur. (2018)
Errata
List of known errors in the course material: