Moving Horizon Extrapolated Iterative Learning Control (EILC)

H.W. Gomma (Egypt)


Iterative Learning Control, Control, Control Theory


The Extrapolated Iterative Learning Control (EILC) was earlier proposed to speed up the learning rate and reduce the executed number of actual iteration compared to the conventional P-type ILC. This paper presents a modified algorithm for EILC, in the sense of introducing the concept of moving horizon while estimating the future tracking errors using an extrapolation technique. This is conducted to reduce the required number of the extrapolated errors, which in turn avoid possible numerical errors that could emerge. For consolidating the objective of the suggested technique, convergence and stability analysis have been investigated. In addition, the results have been explained using different simulation examples.

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