Aims to provide the fundamental theory of 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. It covers: 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.
System Identification (EE 672)
Programs\Type | Required | Core Elective | Area Elective |
MA-European Studies | |||
MA-European Studies-Non Thesis | |||
MA-Political Science | |||
MA-Political Science-Non Thes | |||
MA-Visual Arts&Vis. Com Des-NT | |||
MA-Visual Arts&Visual Com Des | |||
MS-Bio. Sci. & Bioeng. LFI | |||
MS-Bio. Sci. & Bioeng. LFI-ENG | |||
MS-Biological Sci&Bioeng. | * | ||
MS-Computer Sci.&Eng. LFI | |||
MS-Computer Sci.&Eng. LFI-ENG | |||
MS-Computer Science and Eng. | * | ||
MS-Cyber Security(with thesis) | * | ||
MS-Data Science | |||
MS-Elec. Eng&Comp Sc.LFI-ENG | |||
MS-Electronics Eng&Comp Sc.LFI | |||
MS-Electronics Eng&Computer Sc | * | ||
MS-Electronics Eng. | * | ||
MS-Electronics Eng. LFI | |||
MS-Electronics Eng. LFI-ENG | |||
MS-Energy Techno.&Man. | * | ||
MS-Industrial Eng. LFI-ENG | |||
MS-Industrial Engineering | * | ||
MS-Industrial Engineering LFI | |||
MS-Manufacturing Eng-Non Thes | * | ||
MS-Manufacturing Engineering | * | ||
MS-Materials Sci & Engineering | * | ||
MS-Materials Sci. & Eng. LFI | |||
MS-Materials Sci.&Eng. LFI-ENG | |||
MS-Mathematics | |||
MS-Mechatronics | * | ||
MS-Mechatronics LFI | |||
MS-Mechatronics LFI-ENG | |||
MS-Physics | |||
MS-Physics-Non Thesis | * | ||
MS-Psychology | |||
MS-Psychology-Non Thesis | |||
PHD-Biological Sci&Bioeng. | * | ||
PHD-Comp. Sci and Eng.after UG | * | ||
PHD-Computer Science and Eng. | * | ||
PHD-Cyber Security | * | ||
PHD-Electronics Eng&ComputerSc | * | ||
PHD-Electronics Eng. | * | ||
PHD-Electronics Eng. after UG | * | ||
PHD-Experimental Psychology | |||
PHD-Industrial Engineering | * | ||
PHD-Management | |||
PHD-Manufacturing Eng after UG | * | ||
PHD-Manufacturing Engineering | * | ||
PHD-Materials Sci.&Engineering | * | ||
PHD-Mathematics | |||
PHD-Mechatronics | * | ||
PHD-Mechatronics after UG | * | ||
PHD-Physics | |||
PHD-Physics after UG | |||
PHD-Social Psychology | |||
PHDBIO after UG | * | ||
PHDCYSEC after UG | * | ||
PHDEECS after UG | * | ||
PHDEPSY after UG | |||
PHDIE after UG | * | ||
PHDMAN after UG | |||
PHDMAN after UG-Finance | |||
PHDMAN after UG-Man. and Org. | |||
PHDMAN after UG-Op.&Sup. Cha. | |||
PHDMAN-Finance Area | |||
PHDMAN-Man. and Org. Area | |||
PHDMAN-Op. & Supp. Chain Area | |||
PHDMAT after UG | * | ||
PHDMATH after UG | |||
PHDSPSY after UG |
CONTENT
OBJECTIVE
Objective of the course is to provide graduate students with a strong background in linear and nonlinear system identification to build mathematical models from experimental data.
LEARNING OUTCOME
- select inputs and outputs of a system, and characterize disturbances acting on the system.
- design suitable excitation signals,
- use measured input-output data to build mathematical models,
- solve linear regression problems by least squares methods,
- develop nonlinear NARX and Hammerstein-Wiener models
- preprocess data,
- validate obtained models
Update Date:
ASSESSMENT METHODS and CRITERIA
Percentage (%) | |
Midterm | 35 |
Assignment | 30 |
Individual Project | 35 |
RECOMENDED or REQUIRED READINGS
Textbook |
System Identification, Theory for the User, 2nd Edition, Lennart Ljung, Prentice Hall, 1999. |
Readings |
System Identification, Karel J. Keesman, Springer-Verlag London Limited, 2011 |