Robust identification of a single axis high precision positioning system

Robust control has been studied in recent years as an efficient methodology for the design of highly performing controllers of positioning systems. However, it is necessary to provide accurate nominal model and associated uncertainty bounds to design this type of controllers. The aim of this paper is to robustly identify a single axis high precision positioning system with uncertainties. For a given data set a nominal model is identified then model error modeling techniques are used to handle uncertainties in modeling. To examine the quality of the identified nominal and modeling error models H_infin is designed based on the identified uncertainties. Computer simulation and experimenting with the high precision positioning system verify that the obtained nominal model and modeling error model are reliable and the implemented approach can be used to develop an integrated identification and robust controller.