Abstract: This paper deals with the identification of linear systems using input-output response data. Specifically we focus on nonparametric (finite impulse or step response, FIR or FSR) models widely used in model predictive control. A polynomial model is proposed to reduce the number of parameters needed to represent the model. This leads to parsimonious, yet extremely robust models. The tim...

This paper describes the model identification of control valve dynamics with a time delay. An experimental set-up is used to perform both frequency response and step response measurements on the control valve. An approximate realization algorithm and a new time delay estimation method are applied on the experimental data. The results illustrate that the suggested approach provides a good time d...

Although structural constraints such as model order and time delay have been incorporated in the continuous time system identification since its origin, the constraints on the estimated model parameters were rarely enforced. This paper proposes a continuous time system identification approach with constraints. It shows that by incorporating physical parameter information known a priori as hard ...