Iterative learning control with extended state observer for iteration-varying disturbance rejection

Iterative learning control (ILC) is an effective strategy to deal with repetitive tasks and has been widely applied in industrial systems. Up to now, many control schemes have been proposed to improve the performance of ILC system against iteration-varying disturbances. However, most schemes do not directly utilize disturbance information to attenuate disturbances, which limits the performance of control scheme. In this article, a composite control scheme combining a P-type ILC scheme with disturbance compensation is proposed to improve the performance of systems with iteration-varying disturbances. An extended state observer (ESO) is proposed for disturbance estimates. Then by properly choosing the disturbance compensation gain, the disturbances can be attenuated from the system output. Finally, simulations are carried out to demonstrate the efficiency of the proposed control scheme.