Notice of RetractionNP-D-INP-D-type ILC for a class of nonlinear systems

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

In this paper, we presents a new nonlinear iterative learning control law for a class of nonlinear systems, denoted NP-D-INP-D, which is composed by limiting the action of error in PID learning law, that is, use a bounded nonlinear function of error instead of error, and adding a differential feedback in the integrator of PID learning law to inject the suited damping. By using Bellman-Gronwall lemma, the simple explicit conditions on the learning gains to ensure convergence are provided in the sense of Lambda norm. An attractive feature of NP-D-INP-D-type learning law is that it is of faster convergence speed, better flexibility and higher accuracy. The simulation example demonstrates the effectiveness and advantage of NP-D-INP-D-type learning law.