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Azim, Ch. Fahad
- Global Optimal Solution for Active Noise Control Problem
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Authors
Affiliations
1 Faculty of Engineering Sciences & Technology, Hamdard University, PK
2 Faculty of Engineering Sciences & Technology, Hamdard University, PK
3 School of EEE, Nanyang Technological University, SG
4 Engineering division, University Malaysia Perlis, SG
1 Faculty of Engineering Sciences & Technology, Hamdard University, PK
2 Faculty of Engineering Sciences & Technology, Hamdard University, PK
3 School of EEE, Nanyang Technological University, SG
4 Engineering division, University Malaysia Perlis, SG
Source
Indian Journal of Science and Technology, Vol 4, No 9 (2011), Pagination: 1015-1020Abstract
This paper presents the global optimal solution for active noise cancellation using Genetic algorithm technique. The conventional active noise control methods such as FXLMS have problem of local minima. The proposed global optimal solution based on Genetic algorithm can handle this problem very well and give batter results. Computer simulation results demonstrate that Genetic algorithm based active noise control system give more optimal results.Keywords
Active Noise Control, Optimal Solution, Genetic AlgorithmReferences
- Delemotte Ch. Carme V and Montassier A (1995) ANR (active noise reduction) in turbo-prop aircraft. Active 95. 607-618.
- Clarkson PM and White PR (1989) Simplified analysis of the LMS adaptive filter using a transfer function approximation. IEEE Trans. ASSP, 35 (7), 987-992.
- Crawford DH and Stewart RW (1997) Adaptive IK. filtered-V algorithms for active noie control, J. Acoust. Soc. Am. 101(4) 2071-2080.
- Dehandschutter W et al, (1995) Active structural acoustic control of structure borne road noise: theory, simulations, and experiments. Active 95. 735-746.
- Erguo Li (2004) A genetic neural fuzzy system and its application in quality prediction in the injection process. Chem. Engg. Commun. 191(3) 335-355.
- Hirayama R, Kida M Kajikawa (2008) An active noise control system for MR noise: A study on an available ANC system in magnetic field. Intl. Conf. on Signal Processing, Beijing, ICSP (9). 2693 – 2696.
- Kuo SM and Hsien-Tsai Wu (2005) Nonlinear adaptive bilinear filters for active noise control systems. IEEE Transactions on Circuits and Systems I. Regular Papers. 52, 617–624.
- Ma RP and Sinha A (1996) A neural network based active vibration absorber with state feedback control. Letters to Editor. J. Sound & Vibration. 190(1), 121-128.
- Milani AA and Panahi IMS Loizou (2009) A new delayless subband adaptive filtering algorithm for active noise control systems, audio, speech, and language processing. IEEE Transact. 17, 1038–1045.
- Omar Ali Beg and Vali uddin (2009) Implementation of genetic algorithms for parameter estimation of LTI systems. 2nd IEEE Intl. Conf. Computer Control and Communication. Karachi, IEEE- IC-4 (2). 71-76.
- Rahman MA (2001) A flexible way to generate PWMSHE switching patterns using genetic algorithm. Sixteenth Annual IEEE Applied Power Electronics Conference and Exposition (Cat No 01CH37181) APEC-01. 1133.
- Smith SP et al (1996) Active control of low-frequency broadband jet engine exhaust noise, Noise Control Eng. J. 44(1), 45-52.
- Sutton TJ, Elliot SJ and Moore I (1991) Use of nonlinear controllers in the active attenuation of road noise inside cars. Proc. Recent Advances in Active Control of Sound and Vibration. Technomic Publ. Inc., Pennsylvania. pp: 932.