By Topic

A Particle-Swarm-Optimization-Based Decentralized Nonlinear Active Noise Control System

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
George, N.V. ; Sch. of Electr. Sci., Indian Inst. of Technol. Bhubaneswar, Bhubaneswar, India ; Panda, G.

This paper proposes a functional-link-artificial-neural-network-based (FLANN) multichannel nonlinear active noise control (ANC) system trained using a particle swarm optimization (PSO) algorithm suitable for nonlinear noise processes. The use of PSO algorithm in a multichannel ANC environment not only reduces the local minima problem but also removes the requirement of computationally expensive modeling of the secondary-path transfer functions. A decentralized version of a multichannel nonlinear ANC is also developed, which facilitates scaling up of an existing ANC setup without rederiving the learning rules. This is possible as the controller module of each channel is independent of others. Simulation study of the two new multichannel ANC systems demonstrates comparable mitigation performance. However, the decentralized one is preferred to as it possesses the added advantage of scalability.

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:61 ,  Issue: 12 )