Performance Evaluation of Different Active Noise Control (ANC) Algorithms for Attenuating Noise in a Duct

Abstract: Adaptive filter algorithms are extensively use in active control applications and the availability of low cost powerful digital signal processor (DSP) platforms has opened the way for new applications and further research opportunities in e.g. the active control area. The field of active control demands a solid exposure to practical systems and DSP platforms for a comprehensive understanding of the theory involved. Traditional laboratory experiments prove to be insufficient to fulfill these demands and need to be complemented with more flexible and economic remotely controlled laboratories. The purpose of this thesis project is to implement a number of different adaptive control algorithms in the recently developed remotely controlled Virtual Instrument Systems in Reality (VISIR) ANC/DSP remote laboratory at Blekinge Institute of Technology and to evaluate the performance of these algorithms in the remote laboratory. In this thesis, performance of different filtered-x versions adaptive algorithms (NLMS, LLMS, RLS and FuRLMS) has been evaluated in a remote Laboratory. The adaptive algorithms were implemented remotely on a Texas Instrument DSP TMS320C6713 in an ANC system to attenuate low frequency noise which ranges from 0-200 Hz in a circular ventilation duct using single channel feed forward control. Results show that the remote lab can handle complex and advanced control algorithms. These algorithms were tested and it was found that remote lab works effectively and the achieved attenuation level for the algorithms used on the duct system is comparable to similar applications. Keywords: Active Noise Control, Adaptive Algorithms, L-LMS, N-LMS, FuLMS, RLS