Fictitious Reference Iterative Tuning of Internal Model Controllers for Nonlinear Systems with Hysteresis

In this paper, we propose a data-driven tuning method of internal model controllers (which is abbreviated as IMC) for nonlinear systems with hysteresis. We utilize fictitious reference iterative tuning (which is abbreviated as FRIT), which yields the desired controller parameter with only one-shot experimental data without any mathematical models of a plant, to obtain the desired parameter of the IMC in which a mathematical model consisting of not only a dynamical linear part but also static hysteresis one is implemented. As a result, our proposed method enables us to obtain not only a desirable controller but also a mathematical model of the nonlinear system with hysteresis.