Uncertain parameters variable structure neural network identifier in spherical actuator control system

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

Abstract

Owing to spherical actuator control system uncertain parameters generated control errors, our project established offline learning neural network identifier to correct systematic errors. But BP neural network identifier only learning or training offline, which can not be used for errors correcting online, that means control accuracy is susceptible to interference field. Therefore, this paper proposes a variable structure BP (VSBP) neural network identification algorithm to meet the needs of the online error correction control system. The simulation results show that VSBP neural network identifier solved the problem that BP neural network identifier can not meet the needs of the online error correction control system, improved noise immunity and reliability of the spherical actuator control system.

Original languageEnglish
Title of host publicationCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages574-579
Number of pages6
ISBN (Electronic)9781467383189
DOIs
StatePublished - 20 Jan 2017
Event7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016 - Nanjing, Jiangsu, China
Duration: 12 Aug 201614 Aug 2016

Publication series

NameCGNCC 2016 - 2016 IEEE Chinese Guidance, Navigation and Control Conference

Conference

Conference7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016
Country/TerritoryChina
CityNanjing, Jiangsu
Period12/08/1614/08/16

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