SAC for Nonlinear Systems Using Elman Recurrent Neural Networks

• LU Jianming

  The Graduate School of Science and Technology, Chiba University

• PHUAH Jiunshian

  The Graduate School of Science and Technology, Chiba University

• YAHAGI Takashi

  The Graduate School of Science and Technology, Chiba University

抄録

This paper presents a method of simple adaptive control (SAC) for nonlinear systems using Elman recurrent neural networks (ERNNs). The control input is given by the sum of the output of a simple adaptive controller and the output of the ERNN. The ERNN is used to compensate the nonlinearity of plant dynamics that is not taken into consideration in the usual SAC. The role of the ERNN is to construct a linearized model by minimizing the output error caused by nonlinearities in the control systems.

収録刊行物

• IEICE transactions on fundamentals of electronics, communications and computer sciences

  IEICE transactions on fundamentals of electronics, communications and computer sciences 85 (8), 1831-1840, 2002-08-01

  一般社団法人電子情報通信学会

キーワード

• SAC
• nonlinear system
• Elman recurrent neural network

詳細情報

• CRID: 1572543027240106752
• NII論文ID: 110003209222
• NII書誌ID: AA10826239
• ISSN: 09168508
• 本文言語コード: en
• データソース種別:
  • CiNii Articles