Active Disturbance Rejection Based Repetitive Learning Control With Applications in Power Inverters

A novel active disturbance rejection based repetitive learning control scheme, including three channels, namely, feedforward, feedback, and disturbance rejection channels, is investigated. The goal of this work is to achieve a high-quality output voltage and robustness to disturbances and uncertainties in the inverter system. The mathematics model of the inverter is replaced by a chain of two integrators to avoid model identification and time-varying parameter estimation when designing the controller. The ignored system dynamics, the uncertainties, and the nonrepetitive factors caused by nonrepetitive disturbances are all defined as part of the total disturbance to be estimated and compensated for, which decreases the controller sensitivity for the system parameters and operating environment. The stability conditions of the control system scheme along the periods are analyzed, and the mitigation of different frequency-band disturbances using the combination control scheme is demonstrated on the frequency spectrum. Finally, the algorithm is validated on a hardware platform, and the tolerability of varying parameters is tested.