Multimodel repetitive–predictive control of nonlinear systems: rejection of unknown non-stationary sinusoidal disturbances

ABSTRACT In the present work, we propose a supervised multimodel repetitive–predictive control scheme for discrete-time nonlinear systems in order to reject unknown non-stationary sinusoidal disturbances and to track reference trajectory. The nonlinear system is described by the decoupled state multimodel. Also, a non-stationary sinusoidal unknown input multi-observer is used to estimate the state and the unknown non-stationary sinusoidal disturbances simultaneously. The estimate of the disturbances is exploited by the magnitude–phase-locked loop (MPLL) approach to reconstruct the accurate disturbance period used to develop a robust supervised multi-rejector. The proposed control strategy provides good closed-loop performance despite the changes of the disturbance characteristics. A simulation example is provided to illustrate the significance of the proposed multi-rejector.

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