Neural Network Control of Nonlinear Time-delay System with Unknown Dead-Zone and Its Application to a Robotic Servo System

J Na, G Herrmann, X Ren

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

    Abstract

    An adaptive control is proposed for a class of nonlinear systems with unknown time-varying delays and a dead-zone input. Taking the dead-zone as a part of the system dynamics, the construction of the dead-zone inverse model is not needed and thus the characteristic parameters of the dead-zone are not necessarily known. Unknown time delays are handled by introducing improved Lyapunov-Krasovskii functions, where the requirements on the delayed functions/ control coefficients are further relaxed without the singularity problem. A novel high-order neural network with only a scalar weight parameter is developed to approximate unknown nonlinearities. The closed-loop system is proved to be semi-globally uniformly ultimately bounded (SGUUB). Experiments on a robotic servo system are provided to verify the reliability of the presented method.
    Original languageEnglish
    Title of host publicationTrends in Intelligent Robotics 13th FIRA Robot World Congress, FIRA 2010, Bangalore, India, September 15-17, 2010. Proceedings
    EditorsPrahlad Vadakkepat, Jong-Hwan Kim, Norbert Jesse, Abdullah Al Mamun, Tan Kok Kiong, Jacky Baltes, John Anderson, Igor Verner, David Ahlgren
    PublisherSpringer Nature
    Pages338-345
    Number of pages8
    ISBN (Print)3642158099
    DOIs
    Publication statusPublished - 2010

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