Adaptive control of Wiener-type nonlinear systems using neural networks

Osamu Yamanaka, Naoto Yoshizawa, Hiromitsu Ohmori, Akira Sano

Research output: Contribution to journalArticlepeer-review


This paper proposes new adaptive control schemes with neural networks for Weiner-type nonlinear systems which have output nonlinearity. First, by adopting a robust adaptive control law and a functional link network (FLN), we present an adaptive linearizing scheme as a primary step for a model reference control scheme, where the FLN compensates the output nonlinearity. Second, we analyze the stability of the adaptive linearizing scheme by using a robust adaptive control technique, and demonstrate that all of the parameters are bounded and that the boundedness of all of the signals in the closed loop is guaranteed under some reasonable conditions. Third, based on the linearizing scheme, we present a new direct model reference adaptive control scheme by choosing the reference output appropriately. The stability of the system is guaranteed under several conditions in a similar manner. Finally, we illustrate the effectiveness of the proposed scheme through some numerical examples.

Original languageEnglish
Pages (from-to)37-48
Number of pages12
JournalElectrical Engineering in Japan (English translation of Denki Gakkai Ronbunshi)
Issue number1
Publication statusPublished - 1998


  • Adaptive control
  • Neural network
  • Nonlinear control
  • Wiener-type nonlinear system

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering


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