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An adaptive iterative learning control strategy for discrete repetitive processes with non-repetitiveness in the iteration domain

Against the variation of plant and the disturbances in the iteration domain, an adaptive iterative learning control strategy in the iteration domain for discrete repetitive processes with non-repetitiveness is proposed. The parameter estimation method and adaptive inverse control scheme are applied. To reduce the adverse impact that made by uncertainty or unknown of plant and eliminate the non-repetitive disturbances, the parameters of plant are identified online (in each trial) and an adaptive iterative learning controller with a disturbance canceller based on adaptive inverse control is built. A simulation example is presented to illustrate the effectiveness of this adaptive control strategy.