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.

KEYWORDS:

• Nonlinear systems
• repetitive–predictive control
• non-stationary sinusoidal disturbances
• magnitude–phase-locked loop (MPLL)
• multi-observer
• disturbance rejection

Disclosure statement

No potential conflict of interest was reported by the authors.