A switching approach to repetitive control for Takagi-Sugeno fuzzy systems

Repetitive control has learning properties and exhibits high accuracy in periodic control but struggles with nonlinearities and disturbances. To address this issue, the study presents a composite method of repetitive control and equivalent input disturbance based on the TakagiSugeno fuzzy model. The control structure takes into account both the continuous-discrete two-dimensional characteristics of the repetitive control and the membership function of the fuzzy system. As the first component of the control configuration, a repetitive controller is adopted for the high-precision tracking of periodic references. Then, an equivalent-input- disturbance estimator is used to compensate for exogenous disturbances. The closed-loop system is stabilized using the state feedback and the state observer. To ensure stability, membership function-dependent Lyapunov candidates are used to derive a less conservative stability condition. Consequently, all gains in the controller switch with the derivative sign of the premise variables. Finally, the developed approach is validated through comparisons with typical methods, demonstrating its effectiveness and advantages.