Loop-shaping controller design from input-output data

An integrated identification and controller design approach, based on loop-shaping principles, is presented. Starting with time-domain input-output data, a coprime factorization of the plant is identified using linear least-squares techniques. The residual error from the identification is then used to obtain estimates of the coprime factor uncertainty that are translated to sensitivity and complementary sensitivity bounds for the closed-loop system. These bounds serve as a guide for the selection of a target loop and the controller is designed using H_∞ tools. An application on a paper machine simulator is also presented, illustrating the main ideas of the approach