The main problem in system identification is deriving mathematical models of dynamical systems (for transfer function, state-space) from data. Such problem arises for example in control, when the complexity of a model or lack of physical insight prevent the development of a model from first principles to be used in designing a controller.
The algorithms to solve the system identification problem rely, for the linear case, on mathematical methodologies formalised with (relatively) simple linear algebra.
The objective of this course is to give a broad but non superficial introduction to some of the main themes in system identification of discrete-time systems: the use of Hankel matrices and of regression and algebraic structures based on time shifts to derive transfer-function and state-space models.
Pre-requisite: ELEC2220 or ELEC2226