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  • 标题:Model Reference Adaptive Neural Control of a Variable Structure System
  • 本地全文:下载
  • 作者:M. Bonilla ; I. Baruch ; J. Flores
  • 期刊名称:Cybernetics and Information Technologies
  • 印刷版ISSN:1311-9702
  • 电子版ISSN:1314-4081
  • 出版年度:2003
  • 卷号:3
  • 期号:2
  • 出版社:Bulgarian Academy of Science
  • 摘要:The aim of this paper is to propose a model reference adaptive neural control of a variable structure plant, described by an implicit realization with variable order and parameters, using only output feedback. The neural control scheme proposed is composed by two recurrent neural networks, named: neuro-identifier and neuro-controller. A variable structure plant model together with the realized adaptive neural control are simulated by means of the MatLab-Simulink and the obtained simulation results are compared with those obtained by the use of an ideal implicit control, applying the true descriptor variable. The simulation results show a great similarity of the obtained graphics for both control schemes, which demonstrated the applicability of the proposed adaptive neural control.
  • 关键词:Model reference adaptive control; variable structure plant; recurrent neural ;networks; backpropagation learning
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