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论文类型：期刊论文

发表时间：2013-01-01

发表刊物：ICIC Express Letters, Part B: Applications

收录刊物：EI、Scopus

卷号：4

期号：6

页面范围：1691-1696

ISSN号：21852766

摘要：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.