Fictitious reference iterative tuning based on variance evaluation for disturbance attenuation in non-minimum phase plants

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Disturbance attenuation can be realized through Fictitious Reference Iterative Tuning (FRIT) based on variance evaluation. However, this method proposed in the previous work cannot be applied to Non-Minimum Phase (NMP) plants, because unstable pole-zero cancellation results in internal instability. Thus, the present work proposes a disturbance attenuation FRIT for NMP plants. The underlying controller in the proposed approach is an H 2 optimal controller, which can avoid unstable pole-zero cancellation with the help of a generalized interactor. The parameterized possible minimum variance is introduced to the proposed data-driven cost function because the possible minimum variance by the H 2 optimal controller depends on the unknown plant parameters. The paper proves that optimizing the data-driven cost function obtains simultaneously both the optimum controller and the plant parameters. The validity of the proposed method is demonstrated through a numerical example.