Decentralized Neuro-Fuzzy Control of a Class of Nonlinear Systems

  • Miguel A. Hernández
  • Yu Tang
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 5)

A decentralized control based on recurrent neuro-fuzzy networks is proposed for a class of nonlinear systems. It consists of an adaptive component and a uncertainty compensation component. First the control law is designed using the state feedback, and the semiglobal stability is established. Then, by means of a highgain observer, this control law uses only the output feedback. The main features of the proposed scheme are its robustness against uncertainties and its simplicity of implementation. To illustrate the proposed scheme, experiments on a 2-degree-of-freedom robot are included.


IEEE Transaction Tracking Error Output Feedback Output Feedback Control Decentralize Control 


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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Miguel A. Hernández
    • 1
  • Yu Tang
    • 1
  1. 1.Faculty of EngineeringNational University of MexicoMexicoMexico

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