Non-model self-learning control of nonlinear system

  • Authors:

  • Wang PeiFeng;Li Yang;Cai MingWei;Wang JiChao;Li QingRu

  • Affiliations:

  • HeBei University of Science and Technology, Shijiazhuang, China;Shijiazhuang Science Technology & Information College, Shijiazhuang, China;HeBei University of Science and Technology, Shijiazhuang, China;HeBei University of Science and Technology, Shijiazhuang, China;Hebei Normal University, Shijiazhuang, China

  • Venue:
  • Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human
  • Year:
  • 2009

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Abstract

In this paper, one method of non-model error self-learning control of inverse system based on BP networks is presented. The input and output of the system is identified rapidly by BP networks and its momentum BP algorithm. Error controller is constructed simultaneity. The weight matrix of the error controller is dynamically adjusted and transferred to reality self-learning and adaptive control of unknown non-linear systems. The non-linear system simulation example based on MATLAB7.0 shows this control method is effective.