Title :
Active Noise Cancellation Without Secondary Path Identification by Using an Adaptive Genetic Algorithm
Author :
Chang, Cheng-Yuan ; Chen, Deng-Rui
Author_Institution :
Dept. of Electr. Eng., Chung Yuan Christian Univ., Jhongli, Taiwan
Abstract :
This paper presents an adaptive genetic algorithm (AGA) for an active noise control (ANC) system. The conventional ANC system often implements the filtered extended least mean square (FXLMS) algorithm to update the coefficients of the linear finite-impulse response (FIR) and nonlinear Volterra filters, owing to its simplicity; meanwhile, the FXLMS algorithm may converge to local minima. In this paper, the FXLMS algorithm is replaced with an AGA to prevent the local minima problem. Additionally, the proposed AGA method does not require identifying the secondary path for the ANC, explaining why no plant measurement is necessary when designing an AGA-based ANC system. Simulation results demonstrate that the effectiveness of the proposed AGA method can suppress the nonlinear noise interference under several situations without clearly identifying the secondary path.
Keywords :
FIR filters; active noise control; genetic algorithms; least mean squares methods; nonlinear filters; active noise cancellation; active noise control system; adaptive genetic algorithm; filtered extended least mean square; linear finite-impulse response; nonlinear Volterra filters; nonlinear noise interference; secondary path identification; Active noise control (ANC); adaptive genetic algorithm (AGA); local minima; plant measurement; secondary path;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2009.2036410