Quasi-Feedforward and Feedback Control for Random Step Shift Disturbance Models

Abstract

Process monitoring and process adjustment strategies are two important parts of the process improvement methods, and they are often considered separately but should be integrated together. Integrated moving average (IMA) model is the most common disturbance model, and step shift model is one type of more complicated disturbance model that often exists in many real applications. In this paper we investigate the case when IMA background disturbance is subject to random step shifts with a certain probability. We propose a process adjustment procedure with feedback control, together with a so-called quasi-feedforward control based on process monitoring of the output errors. This control strategy was proved to be very robust against parameter misspecifications in the disturbance model. We also further investigate the effects of type I and type II errors in process adjustment on this IMA plus random step shift disturbance model.