In system modelling the choice of the model structure plays an important role. This model structure specifies the mathematical expressions to describe the system and the parameters that are considered to play a role. By setting correct values for the parameters, it is possible to optimise the agreement between the behaviour of the model and system.
Topics of this course are: The selection of the model structure, parameter estimation and the design of identification experiments for that purpose. One part is about socalled system identification, where mathematical models are used. Usually the parameters do not have a physical meaning. The focus is on a limited number of standard model structures for linear systems. In addition, attention will be paid to more general parameter estimates in time and frequency domain. Nonlinear systems are also tackled and the parameters usually have a physical meaning.
