Nonlinear indirect adaptive decoupling control based on neural networks and multiple models

Yue Fu, Tianyou Chai, Hong Wang

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

    Abstract

    In this paper, an indirect adaptive decoupling controller is presented for a class of uncertain nonlinear multivariable discrete time dynamical systems. The indirect adaptive decoupling controller is composed of a linear robust indirect adaptive decoupling controller, a neural network nonlinear indirect adaptive decoupling controller and a switching mechanism. The linear decoupling controller can provide boundedness of the input and output signals, and the nonlinear decoupling controller can improve performance of the system. The purpose of using the switching mechanism is to obtain the improved system performance and stability simultaneously. Theory analysis and simulation results are presented to show the effectiveness of the proposed method. ©2006 IEEE.
    Original languageEnglish
    Title of host publicationProceedings of the American Control Conference|Proc Am Control Conf
    Pages3692-3697
    Number of pages5
    Volume2006
    Publication statusPublished - 2006
    Event2006 American Control Conference - Minneapolis, MN
    Duration: 1 Jul 2006 → …

    Conference

    Conference2006 American Control Conference
    CityMinneapolis, MN
    Period1/07/06 → …

    Fingerprint

    Dive into the research topics of 'Nonlinear indirect adaptive decoupling control based on neural networks and multiple models'. Together they form a unique fingerprint.

    Cite this