Design of a robust neuro-controller for complex dynamic systems

Ki Young Song, Madan M. Gupta, Debashisha Jena, Bidyadhar Subudhi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

Design of neuro-controller for complex dynamic systems is a big challenge faced by the researchers. In this paper we present a design of a robust neuro-controller for a dynamic system to make the system response fast with no overshoot. Here the control action decided by the controller completely depends on the value of the error at that point of time. The position feedback which controls the bandwidth of the system as well as the dynamic response is a function of the system error. For large error the position feedback is made large increasing the bandwidth of the system, and for small errors the position feedback value is small. Thus, during the dynamic response of the system the bandwidth of the system is controlled by the system error. Similarly, the velocity feedback which controls the damping in the system is kept very small for large errors, and large for small errors. Thus, in the proposed neuro-controller the position feedback Kp(e,t), and velocity feedback Kv(e,t), are made as a function of error which yields a very fast response with no or very little overshoot.

Original languageEnglish
Title of host publicationNAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event2009 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2009 - Cincinnati, OH, United States
Duration: 14 Jun 200917 Jun 2009

Publication series

NameAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS

Conference

Conference2009 Annual Meeting of the North American Fuzzy Information Processing Society, NAFIPS 2009
Country/TerritoryUnited States
CityCincinnati, OH
Period14/06/0917/06/09

Keywords

  • Neural networks
  • Position feedback
  • Robust neuro-controller
  • Velocity feedback

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