Output L neural dynamic surface control for large inertia servo systems

Guofa Sun, Xuemei Ren

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

Abstract

This paper presents a precise positioning intelligent control scheme for large inertia servo mechanism on the basis of effective compensation of input deadzone nonlinearity. A novel neural observer for estimating system unmeasured states is proposed which is incorporated into dynamic surface control (DSC) algorithm. The output feedback controller and adaptive laws are developed based on Lyapunov stability analysis while Nussbaum function is employed to determine the control direction. L stability validation guarantees both the transient and steady state performance of overall closed loop system signals. The proposed control scheme is demonstrated numerically by applying it to a second order nonlinear system with unknown input deadzone nonlinearity.

Original languageEnglish
Title of host publication3rd IFAC Conference on Intelligent Control and Automation Science, ICONS 2013 - Proceedings
PublisherIFAC Secretariat
Pages555-560
Number of pages6
EditionPART 1
ISBN (Print)9783902823458
DOIs
Publication statusPublished - 2013
Event3rd IFAC Conference on Intelligent Control and Automation Science, ICONS 2013 - Chengdu, China
Duration: 2 Sept 20134 Sept 2013

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
NumberPART 1
Volume3
ISSN (Print)1474-6670

Conference

Conference3rd IFAC Conference on Intelligent Control and Automation Science, ICONS 2013
Country/TerritoryChina
CityChengdu
Period2/09/134/09/13

Keywords

  • Dynamic surface control
  • Large inertia servo systems
  • Neural observer
  • Output feedback

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