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D-type iterative learning control for one-sided Lipschitz nonlinear systems
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DOI：10.1002/rnc.4511.png)
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Abstract
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In this paper, the problem of iterative learning control for a class of nonlinear systems is studied. Here, the nonlinear functions satisfy the one-sided Lipschitz and quadratically inner-bounded conditions. For such nonlinear systems, open-loop and closed-loop D-type learning algorithms are adopted, respectively, and furthermore, the convergence conditions of the D-type learning algorithms are established. It is shown that both algorithms can ensure that the system output converges to the desired trajectory on the whole time interval. Finally, the validity of the presented D-type learning algorithms is verified by a numerical example.
Keywords:
D-type learning algorithms
iterative learning control
nonlinear systems
one-sided Lipschitz
quadratically inner-bounded
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