Design of a Data-driven Reference Generator Using Predicted Data

Abstract

Estimated Response Iterative Tuning (ERIT) has been proposed, which can predict input and output data in advance using only a set of closed loops. On the other hand, a reference governor, which is a mechanism for shaping the reference signal, has been proposed as a method to achieve the target response when it is difficult to readjust the controller. However, this method is difficult to apply to systems that are difficult to model, such as large-scale systems. Therefore, this paper proposes a design method for a reference generator that does not require a model, utilizing predicted data calculated by ERIT.