2018
DOI: 10.1155/2018/9010567
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Hybrid Filtered‐x Adaptive Vibration Control with Internal Feedback and Online Identification

Abstract: Active control is an effective way to suppress low-frequency mechanical vibration. However, with applications to submarine equipment, there are still some shortcomings due to vibration coupling and multifrequency complex excitation. In this paper, a novel hybrid improved adaptive control strategy, feedback and online identification filtered-x LMS, namely, FOFxlms, is proposed, which introduces the residual errors to correct variable step-size, uses the estimated primary path to improve online identification, a… Show more

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Cited by 3 publications
(2 citation statements)
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“…Researchers have conducted extensive research on the theoretical model and generation mechanism of target radiated noise modulation spectrum [9][10][11][12][13]. This includes the development of (quasi-)periodic smooth stochastic models and the automatic detection and extraction method of the modulation line spectrum, which has garnered significant attention [14][15][16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%
“…Researchers have conducted extensive research on the theoretical model and generation mechanism of target radiated noise modulation spectrum [9][10][11][12][13]. This includes the development of (quasi-)periodic smooth stochastic models and the automatic detection and extraction method of the modulation line spectrum, which has garnered significant attention [14][15][16][17][18][19].…”
Section: Introductionmentioning
confidence: 99%
“…e weight coefficients of the adaptive controller are adjusted according to the adaptive algorithm that usually is LMS algorithm, so that the mean square value of the vibration response measured by sensor converges to the minimum direction. e developed FxLMS vibration control algorithm has advantages of good convergence and strong adaptability, and does not depend on the accurate model of controlled structure, which has become one of the hotspots of AVC algorithm research [2][3][4][5]. However, in the FxLMS control algorithm, the convergence rate and steadystate error of LMS algorithm are greatly affected by the step size μ.…”
Section: Introductionmentioning
confidence: 99%