Efficient sensing schemes for the active reduction of sound radiation from plates are presented based on error signals derived from spatially weighted plate velocity or near-field pressure. The schemes result in near-optimal reductions as compared to weighting procedures derived from eigenvector or singular vector analysis of the radiation operator. Efficient control configurations are suggested using a, possibly analog, front-end implementing a bank of spatial weighting functions and a digital controller with a minimized number of input and output channels. The performance of different weighting functions is compared, as well as the performance of different frequency-dependent filtering functions. Design rules are given for the sensor spacing, the number of weighting functions, the number of actuators, and the corresponding controller dimensionality.
In this paper, a multichannel adaptive control algorithm is described which has good convergence properties while having relatively small computational complexity. This complexity is similar to that of the filtered-error algorithm. In order to obtain these properties, the algorithm is based on a preprocessing step for the actuator signals using a stable and causal inverse of the minimum-phase part of the transfer path between actuators and error sensors, the secondary path. The latter algorithm is known from the literature as postconditioned filtered-error algorithm, which improves convergence rate for the case that the minimum-phase part of the secondary path increases the eigenvalue spread. However, the convergence rate of this algorithm suffers from delays in the adaptation path because adaptation rates have to be reduced for larger delays. The contribution of this paper is to modify the postconditioned filtered-error scheme in such a way that the adaptation rate can be set to a higher value. Consequently, the scheme also provides good convergence if the system contains significant delays. Furthermore, a regularized extension of the scheme is given which can be used to limit the actuator signals.
In this paper active noise control strategies for noise barriers are presented which are based on the use of sensors near the noise barrier. Virtual error signals are derived from these near-field sensor signals such that reductions of the far-field sound pressure are obtained with the active system. The performance of the control algorithm is compared for far-field error signals, near-field error signals, and virtual far-field error signals, with and without additional reference sensors. The virtual error signals are obtained by using separate transfer functions for the primary sources and secondary sources. These separate transfer functions are determined in such a way that the necessity of the separation of the virtual sensors for the primary field and for the secondary field can be judged by direct comparison. The systems are evaluated for independent broadband and randomly positioned primary sources, changing source spectra, moving sources, and configurations involving a nonvanishing wind speed.
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