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Sliding mode control for electromagnetic satellite formation based on RBF neural network

  • Beihang University

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

Abstract

In this paper, a radial basis function (RBF) neural network based sliding mode control is presented. Taking CW equation as dynamics model, the parameter perturbation and external disturbance has been considered. The controller consists of two parts, one is the feed-forward control, and the other is feedback sliding mode control using RBF neural network. Based on Lyapunov stability theory, the adaptive law of neural network has been obtained. Simulation results suggest that the control scheme can initialize the formation and maintain the relative motion according to the desired trajectory. The inherent chattering of sliding mode control has been weaken and the accuracy of trajectory tracking has greatly improved with the use of RBF neural network.

Original languageEnglish
Title of host publicationProceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016
EditorsJunbao Li
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages532-535
Number of pages4
ISBN (Electronic)9781509011957
DOIs
StatePublished - 5 Dec 2016
Event6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016 - Harbin, Heilongjiang, China
Duration: 21 Jul 201623 Jul 2016

Publication series

NameProceedings - 2016 6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016

Conference

Conference6th International Conference on Instrumentation and Measurement, Computer, Communication and Control, IMCCC 2016
Country/TerritoryChina
CityHarbin, Heilongjiang
Period21/07/1623/07/16

Keywords

  • Electromagnetic satellite
  • Formation flight
  • RBF neural network
  • Sliding mode control

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