Designing response surface model based Run by Run controllers: a new approach

This paper presents a framework for carrying out robust Run by Run (RbR) control via a set-theoretic approach. In particular the RbR controller developed tries to minimize the worst case performance of the plant. This gives us a methodology to handle uncertainty. An interesting consequence of using the set valued approach is that now we can relax the assumptions made on the statistics of the noise. Hence, we can also deal with non-Gaussian and correlated noise. We provide results comparing the performance of the controller to a recursive least squares based controller.