A New Feedback-feedforward Configuration for the Iterative Learning Control of a Class of Discrete-time Systems

This paper presents a new feedback-feedforward configuration for the iterative learning control (ILC) design with feedback, which consists of a feedback and a feedforward component. The feedback integral controller stabilizes the system, and takes the dominant role during the operation, and the feedforward ILC compensates for the repeatable nonlinear/unknown time-varying dynamics and disturbances, thereby enhancing the performance achieved by feedback control alone. As the most favorable point of this control strategy, the feedforward ILC and the feedback control can work either independently or jointly without making efforts to reconfigurate or retune the feedforward/feedback gains. With rigorous analysis, the proposed learning control scheme guarantees the asymptotic convergences along the iteration axis.