Contraction analysis of nonlinear noncausal iterative learning control

Elsevier BV
Publication Type:
Journal Article
Systems and Control Letters, 2020, 136, pp. 104599-104599
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© 2019 Elsevier B.V. Iterative learning control (ILC) is a method for learning input signals for repetitive control tasks. In this paper, we provide a new method based on convex optimization for certifying convergence and estimating convergence rate in ILC schemes involving a nonlinear plant and a noncausal update law, which are common in practice. Using sum-of-squares (SOS) optimization, we compute the convergence rate of an example nonlinear, noncausal ILC system and verify its accuracy in experiment.
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