Optimal fuzzy iterative learning control based on artificial bee colony for vibration control of piezoelectric smart structures

Liang Bai, Yun Wen Feng, Ning Li, Xiao Feng Xue

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Combining P-type iterative learning (IL) control, fuzzy logic control and artificial bee colony (ABC) algorithm, a new optimal fuzzy IL controller is designed for active vibration control of piezoelectric smart structures. In order to accelerate the learning speed of feedback gain, the fuzzy logic controller is integrated into the ANSYS finite element (FE) models by using APDL (ANSYS Parameter Design Language) approach to adjust adaptively the learning gain of P-type IL control. For improving the performance and robustness of the fuzzy logic controller as well as diminishing human intervention in the operation process, ABC algorithm is used to automatically identify the optimal configurations for values in fuzzy query table, fuzzification parameters and defuzzification parameters, and the main program of ABC algorithm is operated in MATLAB. The active vibration equations are driven from the FE equations for the dynamic response of a linear elastic piezoelectric smart structure. Considering the vibrations generated by various external disturbances, the optimal fuzzy IL controller is numerically investigated for a clamped piezoelectric smart plate. Results demonstrate that the proposed control approach makes the feedback gain has a fast learning speed and performs excellent in vibration suppression. This is demonstrated in the results by comparing the new control approach with the P-type IL control.

Original languageEnglish
Pages (from-to)111-132
Number of pages22
JournalJournal of Vibroengineering
Volume21
Issue number1
DOIs
StatePublished - Feb 2019

Keywords

  • Active vibration control
  • Artificial bee colony algorithm
  • Fuzzy logic control
  • P-type IL control
  • Piezoelectric smart structure

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