Eigenvalue equalization applied to the active minimization of engine noise in a mock cabin

A number of active noise control applications involve the need to control multiple stationary frequencies, a single time-varying frequency, or some combination of the two. The most common control approach is typically based on some version of the filtered-x algorithm. For this algorithm, the convergence and tracking speed is dependent on the eigenvalues of the filtered-x autocorrelation matrix, with these eigenvalues being frequency dependent. To maintain stability, the system must be implemented based on the slowest converging frequency that will be encountered, which can lead to significant degradation in the overall performance of the control system. This paper will present an approach which largely overcomes this frequency dependent performance, maintains a relatively simple control implementation, and improves the overall performance of the control system. The control approach is called the eigenvalue equalization filtered-x (EE-FXLMS) algorithm and its effectiveness is demonstrated through an application to engine noise in a mock cabin. Experimental results show that the EE-FXLMS algorithm provides as much as 3.5 dB additional attenuation compared to the normal filtered-x algorithm. a Email address: [email protected] b Email address: [email protected] c Email address: [email protected] d Email address: [email protected]