Skip to Main Content
In this paper one presents an algorithm for a DC motor parameters identification from sample data using the distribution approach. While most of the latest methods used in identification utilize a discrete-time model, the distribution method is an alternative approach to directly identify a continuous-time model from discrete-time data. The relation between the state variables is represented by functionals using techniques from distribution theory. Based on these relations, an algorithm for off-line parameter identification is developed. The method is applied to identify the parametric model of a real experimental platform and of a simulated model.