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Analysis and implementation of improved multi‐input multi‐output filtered‐X least mean square algorithm for active structural vibration control
Author(s) -
Huang Quanzhen,
Zhu Xiaojin,
Gao Zhiyuan,
Gao Shouwei,
Jiang Enyu
Publication year - 2013
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1541
Subject(s) - control theory (sociology) , signal (programming language) , least mean squares filter , algorithm , controller (irrigation) , vibration , vibration control , residual , system identification , noise (video) , square (algebra) , active vibration control , filter (signal processing) , engineering , computer science , mathematics , adaptive filter , control (management) , artificial intelligence , acoustics , software engineering , image (mathematics) , data modeling , biology , geometry , agronomy , physics , electrical engineering , programming language
An improved multi‐input multi‐output filtered‐X least mean square‐based vibration control algorithm is proposed to solve the reference signal extraction problem for active vibration control system. The reference signal is constructed by the controller parameters and the vibration residual signal extracted directly from the vibrating structure, which is related to the external disturbance signal. Meanwhile, an FIR filter is adopted for online identification by adding white noise signal to the controller output as identification input signal; the identified model is substituted into the control algorithm, and the online secondary path identification is realized. Thus, the practical application problem of filtered‐X least mean square algorithm is solved. The simulations and experiments show that the proposed algorithm is reliable and effective with good control performance. Copyright © 2013 John Wiley & Sons, Ltd.