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Indexed by:期刊论文

Date of Publication:2013-01-01

Journal:ICIC Express Letters, Part B: Applications

Included Journals:EI、Scopus

Volume:4

Issue:6

Page Number:1691-1696

ISSN No.:21852766

Abstract:The improvement designs for the model-free learning adaptive control (MFLAC) based on multi-innovation (MI) and chaotic genetic algorithms (CGA) are presented in this paper. The application of MI and CGA are to overcome the limitation of the conventional MFLAC design, which cannot guarantee the satisfactory control performance when the controlled system has the characteristic of strong time-varied nonlinearity. Numerical results for the different nonlinear systems are shown to illustrate the effectiveness of the improved designs. ? 2013 ICIC International.