Applying modular networks and fuzzy-logic controllers to nonlinear flexible structures

Hava T. Siegelmann, Azmon Ofri, Hugo Guterman

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper describes a computer simulation analysis of modular networks and fuzzy-logic controllers for the motion control of 2-D nonlinear flexible structures. The Stochastic-Gradient Learning Algorithm using modular networks is presented and applied as two inputs one output controller. The self learning process of the Modular Networks consists of a set of LQR. Each one of the LQR was optimized to control a different zone, a state space. The trained controller is used to actually control the system. The two methods are compared quantitatively though the work done, performance index (settling time, energy consumption and over shoot). The comparison shows the advantage of the MN control method having better performance index results and requires less effort in the tuning stage.

Original languageEnglish
Pages96-100
Number of pages5
StatePublished - 1 Dec 1997
Externally publishedYes
EventProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97 - Syracuse, NY, USA
Duration: 21 Sep 199724 Sep 1997

Conference

ConferenceProceedings of the 1997 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS'97
CitySyracuse, NY, USA
Period21/09/9724/09/97

ASJC Scopus subject areas

  • Computer Science (all)
  • Mathematics (all)

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