Fictitious reference iterative tuning of internal model controllers for non-minimum phase plants

Fictitious Reference Iterative Tuning (FRIT) is one of the effective data-based methods for the tuning of the controller parameters with only one-shot experiment. In this paper, we apply FRIT for tuning parameters of the internal model controller (IMC). Particularly, we focus on non-minimum phase (NMP) plants and study how the utilization of FRIT for IMC can be extended to NMP plants. The proposed approach enables us to obtain not only a controller for the desired tracking property but also a mathematical model of the controlled plant, which means that we can simultaneously obtain a model of the plant and a desired controller.