Simultaneous Updating of Model and Controller Based on Fictitious Reference Iterative Tuning

摘要

In this paper, we provide a new method for updating a mathematical model of a plant and a controller, simultaneously, by using only one-shot experimental data. Here, we propose a fictitious controller which is described by the following triple: a nominal model of the plant, an initial controller designed for the nominal model, and a parameterized model of the plant. In addition, we introduce a cost function which involves the fictitious controller, the nominal model, and the actual experimental data of the closed loop with the initial controller. Then, for this very reason of the minimization of the introduced cost function, we show that utilizing the fictitious reference iterative tuning, which was proposed by the authors, enables us to obtain both a more accurate model and a more desirable controller than the nominal model and the initial controller, respectively. We also give quantitative evaluation of the difference between the nominal model and the updated one, and that between the initial controller and the updated one. Finally, we give examples in order to illustrate the validity of the proposed method.