DSP-based direct neural control for thrust active magnetic bearing learned through adaptive differential evolution

Syuan-Yi Chen, Min Han Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A digital signal processor (DSP)-based direct recurrent wavelet neural network (RWNN) controller is proposed to control the rotor position of a thrust active magnetic bearing (TAMB) system learned through adaptive differential evolution (ADE). First, the dynamic analysis of the TAMB with differential driving mode (DDM) is derived. Subsequently, due to the exact dynamic model of TAMB system is absent; a RWNN is adopted to deal with the highly nonlinear TAMB system for the tracking of reference trajectory. Moreover, Due to the gradient descent method is used in back propagation (BP) to derive the on-line learning algorithm for the RWNN; it may reach the local optimal solution due to the inappropriate initial values. Therefore, an ADE algorithm is adopted to optimize the initial network parameters including connective weights, translations and dilations for the RWNN controller. Finally, a DSP with PowerPC 440 processor and real time VxWorks OS is used for implementing the RWNN-ADE controller for TAMB system. Experimental results show the high-accuracy control performance of the proposed RWNN-ADE controlled TAMB system.

Original languageEnglish
Title of host publicationCACS 2015 - 2015 CACS International Automatic Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages96-101
Number of pages6
ISBN (Electronic)9781467365734
DOIs
Publication statusPublished - 2016 Jan 11
Event9th International Automatic Control Conference, CACS 2015 - Yilan, Taiwan
Duration: 2015 Nov 182015 Nov 20

Publication series

NameCACS 2015 - 2015 CACS International Automatic Control Conference

Other

Other9th International Automatic Control Conference, CACS 2015
CountryTaiwan
CityYilan
Period15/11/1815/11/20

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'DSP-based direct neural control for thrust active magnetic bearing learned through adaptive differential evolution'. Together they form a unique fingerprint.

Cite this