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Indexed by:期刊论文

Date of Publication:2014-10-15

Journal:Journal of Computational Information Systems

Included Journals:EI、Scopus

Volume:10

Issue:20

Page Number:8813-8820

ISSN No.:15539105

Abstract:We develop a novel iterative learning control (ILC) algorithm for sampled nonlinear systems. Damped Newton-method proposed here is used to solve problems of local convergence algorithms in iterative learning control. According to a particular iteration-varying learning gain, iterative learning law is constructed to remove rigorous condition of initial value close enough to the unknown desired input. Furthermore, a detailed convergence analysis is given. And the choice of parameter is considered in algorithm realization. It is shown theoretically that this algorithm can be ensured to be convergent in quadratic convergence speed without additional initial requirement. With the aid of simulation results, effectiveness of the proposed algorithm is illustrated. 1553-9105/Copyright ? 2014 Binary Information Press