A On-Line Secondary Path Modeling Frequency Domain Active Noise Control Algorithm Based on the Kalman Filter
نویسندگان
چکیده
A new frequency domain ANC algorithm based on the Kalman filter is presented. This algorithm has on-line secondary path modeling and is designed to minimize the effects of large secondary path changes on the acoustic noise level. It is based on the Overall Modeling Algorithm with a careful controller and estimation of the secondary path changes. Due to its frequency domain implementation the system will not work well as a predictor but is suitable for feed-forward broadband active noise control applications. The Kalman filter estimates the primary and secondary paths. The estimates and their variances are used to determine the optimal controller. Because the controller is only based on secondary and primary path models, it is much more robust to secondary path changes than other approaches based on the FX-LMS, allowing for faster convergence.
منابع مشابه
An Optimized Online Secondary Path Modeling Method for Single-Channel Feedback ANC Systems
This paper proposes a new method for online secondary path modeling in feedback active noise control (ANC) systems. In practical cases, the secondary path is usually time-varying. For these cases, online modeling of secondary path is required to ensure convergence of the system. In literature the secondary path estimation is usually performed offline, prior to online modeling, where in the prop...
متن کاملA Robust Feedforward Active Noise Control System with a Variable Step-Size FxLMS Algorithm: Designing a New Online Secondary Path Modelling Method
Several approaches have been introduced in literature for active noise control (ANC)systems. Since Filtered-x-Least Mean Square (FxLMS) algorithm appears to be the best choice as acontroller filter. Researchers tend to improve performance of ANC systems by enhancing andmodifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANCapplications an online secondary pat...
متن کاملTuning of Extended Kalman Filter using Self-adaptive Differential Evolution Algorithm for Sensorless Permanent Magnet Synchronous Motor Drive
In this paper, a novel method based on a combination of Extended Kalman Filter (EKF) with Self-adaptive Differential Evolution (SaDE) algorithm to estimate rotor position, speed and machine states for a Permanent Magnet Synchronous Motor (PMSM) is proposed. In the proposed method, as a first step SaDE algorithm is used to tune the noise covariance matrices of state noise and measurement noise i...
متن کاملDesign and Implementation of a Kalman Filter-Based Time-Varying Harmonics Analyzer
Nowadays with increasing use of numerous nonlinear loads, voltage and current harmonics in power systems are one of the most important problems power engineers encounter. Many of these nonlinear loads, because of their dynamic natures, inject time-varying harmonics into power system. Common techniques applied for harmonics measurement and assessment such as FFT have significant errors in presen...
متن کاملThe Kalman Filter in Active Noise Control
Most Active Noise Control (ANC) systems use some form of the LMS [5][7] algorithm due to its reduced computational complexity. However, the problems associated with it are well-known, namely slow convergence and high sensitivity to the eigenvalue spread [3][7]. To overcome this problems the RLS algorithm is often used, but it is now widely known, that the RLS loses many of its good properties f...
متن کامل