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.M. Ren

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

11 Citations (Scopus)

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.
Translated title of the contributionNeural Network Control of Nonlinear Time-delay System with Unknown Dead-Zone and Its Application to a Robotic Servo System
Original languageEnglish
Title of host publicationTrends in Intelligent Robotics
Subtitle of host publication13th FIRA Robot World Congress, FIRA 2010, Bangalore, India, September 15-17, 2010. Proceedings
PublisherSpringer Berlin Heidelberg
Number of pages0
DOIs
Publication statusPublished - 2010

Bibliographical note

Conference Organiser: FIRA, National University of Singapore, KAIST

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