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An adaptive variable step-size algorithm is proposed in this paper to address the impact of the real-time acoustic feedback and the real-time secondary path identification on the overall noise reduction performance of an active noise control system. An automated adjustment weight factor is introduced in the algorithm to accelerate the convergence of the acoustic feedback path as well as the secondary path identification, and to prevent possible system divergence. It is shown in this study that the proposed algorithm can resolve the trade-off between a fast convergence and a low misalignment of the virtual and the actual control paths typically found in conventional algorithms. An optimized control structure is also proposed in the study by enabling an adaptive gain adjustment based on the output of the auxiliary filter to enhance the practicality of the control system. The effectiveness of the algorithm is tested using two simulated multi-component signals and a broadband noise signal, and the results confirm that the proposed algorithm can achieve a good noise reduction with only a few iterations. [ABSTRACT FROM AUTHOR]

Recent studies on diffusion adaptation for distributed active noise control (DANC) systems have attracted significant research interest due to their balance between computational burden and stability compared to conventional centralized and decentralized adaptation schemes. The conventional multitask diffusion FxLMS algorithm assumes that the converged solutions of all control filters are consistent to each other, which is unrealistic in practice hence results in inferior performance in noise reduction. An augmented diffusion FxLMS algorithm has been proposed to overcome this problem, which adopts a neighborhood-wide adaptation and node-based combination approach to mitigate the bias in the converged solution of the multitask diffusion algorithms. However, the improvement comes at the expense of a higher computational burden and communication cost. All existing DANC systems, including the multitask and augmented diffusion algorithms, assume one-way communication between nodes. By contrast, this paper proposes a bidirectional communication scheme for the augmented diffusion algorithm to further reduce the memory requirement, computational burden, and communication cost. Simulation results in the free field and with measured room impulse responses both demonstrate that the proposed augmented diffusion algorithm with bidirectional communication can achieve a faster convergence speed than that based on one-way communication with a lower memory, computation, and communication burden. [ABSTRACT FROM AUTHOR]

The phase-shifting based active noise control (ANC) algorithm without secondary path modeling is appealing due to its simple implementation and high computational efficiency. However, the algorithm suffers from the influence of an implicit circular convolution caused by directly applying the most appropriate phase shift to the reference signal in the frequency domain. The implicit circular convolution results in a poor linear relationship between the phase-shifted reference signal and the error signal, which considerably degrades the convergence performance of the ANC system. In this paper, two methods are proposed to deal with this problem. In the first method, the circular wraparound artifacts are removed by the time-domain constraining operation. In the second method, a noncausal phase-shifting filter is used to regularize the phase of the reference signal. Compared with the standard frequency-domain implementation, the two proposed algorithms both eliminate the influence caused by the wraparound artifacts of the circular convolution and improve the linear relationship between the phase-shifted reference signal and the error signal, leading to a higher level of noise attenuation with a tolerable increase in computational complexity. Simulation results validate the better noise attenuation ability of the proposed algorithms. [ABSTRACT FROM AUTHOR]

The active headrest is an important application of active noise control (ANC) where the occupant gets a quiet zone during use. However, its performance degrades due to head movement, which is an important issue. Unlike conventional active headrest algorithm, in the present paper, the two error microphones are attached to a head attachment such as a hat or band so that both error microphones can move along with the head, keeping the relative distance of ears and the microphones intact. The two secondary loudspeakers are kept near to the head, facing the ears. The performance of the active headrest was studied through real-time experimentation considering head movement. The innovation in this paper is that the ANC algorithm uses signals of moving error microphones to tune the controller without re-estimating the secondary path transfer functions. Since, the phase error of secondary path estimates at different head positions remains within ±90°, the secondary paths estimated once, when the head is positioned at the center, can be used for other head positions. This is established through real-time experiments using dSpace 1104 ACE system (dSpace, Germany). [ABSTRACT FROM AUTHOR]

The bin-normalized frequency domain block least mean square (NFBLMS) algorithm is a good choice in the active noise control system due to its benefit of high convergence speed. However, it suffers from a biased steady-state solution with insufficient adaptive filter length, often unavoidable due to the influence of the secondary path. A modified frequency domain block least mean square (MFBLMS) algorithm with guaranteed optimal steady-state performance has been proposed recently. However, its convergence speed is generally lower than that of the NFBLMS algorithm. In this paper, a mixed algorithm combining the NFBLMS and MFBLMS algorithms is proposed based on the analysis of the initial convergence trajectory of the NFBLMS algorithm. An effective switching strategy is designed, enabling the MFBLMS algorithm after the NFBLMS algorithm approaches its steady state and shifting back to the NFBLMS algorithm when the change of environment is detected. The mixed algorithm has both the high convergence speed and the optimal steady-state performance, and its effectiveness is validated by simulations using measured acoustic transfer functions. [ABSTRACT FROM AUTHOR]

Current active noise control systems can cancel noises in a duct effectively. However, they are insufficient for suppressing complex noise fields in time-varying rooms. This paper develops an active noise control system that can cancel tonal noise fields produced by a primary source in a room. The problem of tonal noise field control is formulated as estimating and canceling the outgoing field on a sphere surrounding the primary source. The proposed system limits the energy of the primary source radiating out of the sphere, thereby creating a global quiet zone inside the room. In addition, it removes the need for online secondary path estimation with reduced influence on desired sound fields in the room. A method for estimating the outgoing field on a sphere is presented, together with a wave-domain algorithm for controlling the outgoing field. Simulations and hardware demonstrations show the proposed system can reduce tonal noise fields in a room and over a wide frequency range. [ABSTRACT FROM AUTHOR]

Multi-channel active noise control (ANC) is currently an attractive solution for the attenuation of low-frequency noise fields, in three-dimensional space. This paper develops a controller for the case when the noise source components are sparsely distributed in space. The anti-noise signals are designed as in conventional ANC to minimize the residual errors but with an additional term containing an ll norm regularization applied to the signal magnitude. This results in that only secondary sources close to the noise sources are required to be active for cancellation of sparse noise fields. Adaptive algorithms with low computational complexity and faster convergence speeds are proposed. [ABSTRACT FROM AUTHOR]