A Novel Filtered-X LMS Algorithm and Its Application to Active Noise Control

Bao, Chaoeng; Sas, Paul; Brussel, Hendrik Van

doi:10.1016/b978-0-444-89587-5.50129-8

Cited by 2 publications

(2 citation statements)

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“…Because it has the advantages of simple structure and lower model accuracy, it is widely used in noise cancelation, active vibration control, etc. Bao et al [9] proposed an FXLMS algorithm based on the smallest output error by constructing a virtual system model, which is applied in an active noise control system. In the following year, they studied the rapid convergence of the algorithm and improved the converging speed of the FXLMS algorithm [10].…”

Section: Introductionmentioning

confidence: 99%

“…Bao et al [9] proposed an FXLMS algorithm based on the smallest output error by constructing a virtual system model, which is applied in an active noise control system. In the following year, they studied the rapid convergence of the algorithm and improved the converging speed of the FXLMS algorithm [10]. Douglas [11] proposed a multi-channel FXLMS quick algorithm and applied it to the active noise control system.…”

Section: Introductionmentioning

confidence: 99%

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Analysis and implementation of a structural vibration control algorithm based on an IIR adaptive filter

Huang

Luo

et al. 2013

Smart Mater. Struct.

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With the wide application of large-scale flexible structures in spacecraft, vibration control problems in these structures have become important design issues. The filtered-X least mean square (FXLMS) algorithm is the most popular one in current active vibration control using adaptive filtering. It assumes that the source of interference can be measured and the interference source is considered as the reference signal input to the controller. However, in the actual control system, this assumption is not accurate, because it does not consider the impact of the reference signal on the output feedback signal. In this paper, an adaptive vibration active control algorithm based on an infinite impulse response (IIR) filter structure (FULMS, filtered-U least mean square) is proposed. The algorithm is based on an FXLMS algorithm framework, which replaces the finite impulse response (FIR) filter with an IIR filter. This paper focuses on the structural design of the controller, the process of the FULMS filtering control method, the design of the experimental model object, and the experimental platform construction for the entire control system. The comparison of the FXLMS algorithm with FULMS is theoretically analyzed and experimentally validated. The results show that the FULMS algorithm converges faster and controls better. The design of the FULMS controller is feasible and effective and has greater value in practical applications of aerospace engineering.

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Section: Introductionmentioning

confidence: 99%