Abstract
This electronic document is a “live” template. For a class of nonlinear continuous multivariable (NCM) systems under the condition of one-sided Lipschitz and quadratic inner-bounded, an iterative learning control (ILC) algorithm is proposed. The open-loop and closed-loop forms of the proposed algorithm is considered in this paper, and the mathematical methods such as $\lambda-$norm and its related characteristics are used to analyze the convergence of the proposed algorithm. We prove the effectiveness of the proposed algorithm for output tracking of the nonlinear controlled system and give the convergence conditions. Simulation results show that the closed-loop ILC algorithm is more stable than the open-loop ILC algorithm. Compared with the iterative learning control under the classical local Lipschitz condition, the improved algorithm under one-sided Lipschitz and quadratic inner-bounded conditions decrease the constraint condition of the iterative learning control on the controlled system.
Published Version
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