Selected Problems in the Interplay between System Identification and (Robust) Control Design

Prof. Paul Van den Hof (Delft University of Technology)

The enhancement of control systems performance by model identification and subsequent model-based (robust) control design has recently attracted considerable attention. Both the system identification community and the control community have spent considerable efforts in developing a coherent approach to the problem. Typical questions that have to be dealt with are:

* How to model disturbances on measured data in order to arrive at model uncertainty specifications that are tractable for controller robustness analysis and synthesis?

* Which uncertainty structures to use for quantifying model uncertainty in view of stability and performance?

* How to design appropriate experiments that provide the necessary information on plant dynamics that allows for the (re)design of a controller with enhanced performance?

Research into these problems has delivered several attempts for bridging the gap between identification and control theory and technology. In this lecture some of these developments will be highlighted, directing particular attention to the questions how to quantify model uncertainty, which uncertainty structure to choose for robustness verification, the use of closed-loop experimental data for identification, and the use of identification criteria that are motived by control performance cost functions.

A practical example of a wafer stepper (nano-)positioning system will be used to illustrate the achieved results.

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