Intelligent integral backstepping sliding-mode control for piezo-flexural nanopositioning stage

Faa Jeng Lin, Shih Yang Lee

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

3 Scopus citations

Abstract

An intelligent integral backstepping sliding-mode control (IIBSMC) system using a recurrent neural network (RNN) is proposed for the three-dimension motion control of a piezo-flexural nanopositioning stage (PFNS) in this study. Moreover, the RNN estimator is proposed to estimate the lumped uncertainty including the system parameters and external disturbance online. Furthermore, the online tuning law for the training of the parameters of the RNN is derived using the Lyapunov stability theorem. In addition, a robust compensator is proposed to confront the minimum reconstructed error occurred in the IIBSMC system. Finally, some experimental results are given to demonstrate the validity of the proposed IIBSMC system. From the performance measurings of the proportional-integral (PI) control, sliding mode control (SMC), integral backstepping sliding-mode control (IBSMC) and IIBSMC systems, the proposed IIBSMC system has the lowest maximum, average and standard deviation of the position tracking errors for the three-dimension motion control of the PFNS.

Original languageEnglish
Title of host publication2015 IEEE 2nd International Future Energy Electronics Conference, IFEEC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479976577
DOIs
StatePublished - 18 Dec 2015
Event2nd IEEE International Future Energy Electronics Conference, IFEEC 2015 - Taipei, Taiwan
Duration: 1 Nov 20154 Nov 2015

Publication series

Name2015 IEEE 2nd International Future Energy Electronics Conference, IFEEC 2015

Conference

Conference2nd IEEE International Future Energy Electronics Conference, IFEEC 2015
Country/TerritoryTaiwan
CityTaipei
Period1/11/154/11/15

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