Repetitive control mechanism of disturbance rejection using basis function feedback with fuzzy regression approach

Applying a repetitive control mechanism to eliminate disturbances in a mechanical control system has been an important subject of investigation. This paper presents a fuzzy theorem approach for the repetitive control law using basis functions feedback. The law adjusted the command given a feedback control system in order to eliminate tracking errors because of a periodic disturbance. This periodic error is reduced by linear basis functions and by a data classification system using fuzzy set theory. For each category of classified data, multiple regression analysis is applied to the linear model. With data which have been classified into 4 categories and when the data are stabilized, the tracking error of the obtained convergence value of 10 can be reached, illustrating that the proposed fuzzy regression approach is able to satisfactorily reduce the periodic error.