Perspectives on system identification

: System identification is the art and science of building mathematical models of dynamic systems from observed input-output data. It can be seen as the interface between the real world of ions and the mathematical world of control theory and model abstractions. As such, it is an ubiquitous necessity for successful applications. System identification is a very large topic, with different techniques that depend on the character of the models to be estimated: linear, nonlinear, hybrid, nonparametric etc. At the same time, the area can be characterized by a small number of leading principles, e.g. to look for sustainable descriptions by proper decisions in the triangle of model complexity, information contents in the data, and effective validation. The area has many facets and there are many approaches and methods. A tutorial or a survey in a few pages is not quite possible. Instead, this presentation aims at giving an overview of the "science" side, i.e. basic principles and re...

• Type: Journal
• Year: 2010
• Where: ARC
• Authors: Lennart Ljung
• Keywords: ARC 2010, Hardware, Input-output Data, Mathematical Models, System Identification