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Experimental Investigation of Active Vibration Control Using a Filtered-Error Neural Network and Piezoelectric Actuators

  • Yali Zhou
  • Qizhi Zhang
  • Xiaodong Li
  • Woonseng Gan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3498)

Abstract

The filtered-error back-propagation neural network (FEBPNN) algorithm for control of smart structure is investigated experimentally. Piezoelectric actuator is employed to suppress the structural vibration. The controllers based on the FEBPNN algorithm and the filtered-x least mean square (FXLMS) algorithm are implemented on a digital signal processor (DSP) TMS320VC33. The experimental verification tests show that the FEBPNN algorithm is effective for a nonlinear control problem, and has better tracking ability under change of the primary disturbance signal.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yali Zhou
    • 1
  • Qizhi Zhang
    • 1
  • Xiaodong Li
    • 2
  • Woonseng Gan
    • 3
  1. 1.Department of Computer Science and AutomationBeijing Institute of MachineryBeijingChina
  2. 2.Institute of AcousticAcademia SinicaPeople’s Republic of China
  3. 3.School of EEENanyang Technological UniversitySingapore

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