This document summarizes a seminar presentation on fast convergence algorithms for active noise control. Active noise control uses opposite sound waves to cancel out unwanted noise in real-time. Fast convergence algorithms are essential for this to work efficiently. The presentation discusses objectives like noise cancellation and improving vehicle comfort. It explains the working principle of adaptive filters and algorithms. Applications include noise reduction in vehicles, aircraft, factories and homes. The conclusion is that these algorithms have huge potential to create a quieter world by reducing noise in various environments.

1. KLE Dr M S Sheshgiri
College of Engineering and Technology,
Udyambag, Belagavi – 590008
Department of Mechanical Engineering
Seminar Presentation
By
NIRANAJN S KOTAGI
2KL19ME048
“Fast Convergence Algorithms for Active Noise
Controlling”
Under the Guidance of
Prof. B. G. Koujalagi
Assistant Professor
Department of Mechanical Engineering

2. Contents
• Introduction
• Objectives
• Working Principle
• Application
• Conclusion
• Reference

3. Introduction
• Active noise control (ANC) is a technique used to reduce unwanted noise by generating an opposite sound
wave that cancels out the original sound.
• Fast convergence algorithms are essential for ANC systems to operate efficiently and effectively.
• These algorithms rapidly adapt to changes in the noise environment, ensuring that the ANC system can cancel
out noise in real-time.
• One of the most commonly used fast convergence algorithms for ANC is the adaptive filter algorithm. This
algorithm uses a reference signal and an error signal to adjust the filter coefficients in real-time.
• In recent years, advanced adaptive algorithms have attracted much interest in the development of effective
active noise control (ANC) systems.

4. Objectives
• The main objective of the noise cancellation is to estimate the noise signal and to subtract it from original input
signal plus noise signal and hence to obtain the noise free signal.
• With improvement of living standard riding comfort has become an important indicator of choosing a car but the
noise in the car is the key factor affecting the ride comfort.
• The traditional passive noise reduction technology has a good inhibitory effect on high frequency noise but the effect
of low frequency noise is not ideal and the active noise control system solves this problem well.
• This article first analyses the characteristics and components of automobile noise, this paper introduces the principle
of active noise control system, introduces the structure of the feedforward and feedback structure and mixed
structure of active noise control system structure characteristics and performance, and analyses its feasibility for
automobile noise suppression.

5. Working Principle
• The key to the noise reduction performance of noise control system is the output y(n)of the adaptive filter and
the degree of coherence of the primary noise. The higher the coherence of the two signals, the smaller the
residual noise and the better the noise reduction effect . On the contrary, the effect of noise reduction is not
good, and even the noise may be enhanced.
• On the contrary, the effect of noise reduction is not good, and even the noise may be enhanced. So the
selection of adaptive filter and adaptive algorithm is very important.
• Generally speaking, the selection of adaptive filter has two kinds of FIR filter IIR filter, the order number of
IIR filter is low, but the existence of zero pole may cause the instability of the system.

6. Applications
• Fast convergence algorithms for active noise controlling have a wide range of potential applications. One of
the most significant is in the automotive industry, where active noise control systems can be used to reduce
engine noise and improve passenger comfort. Other potential applications include aircraft noise reduction,
industrial noise reduction, and even noise reduction in residential settings.
• As these algorithms continue to evolve and improve, they have the potential to revolutionize the way we think
about noise reduction and create a quieter, more peaceful world.

7. Conclusion
• Fast convergence algorithms for active noise controlling are a rapidly evolving field of study with enormous
potential. By combining the latest advances in adaptive filtering and nonlinear active noise control,
researchers are creating new and innovative ways to reduce unwanted sound in various environments.
• As these algorithms continue to improve, we can expect to see them applied in a wide range of settings, from
cars and airplanes to factories and homes. The future of noise reduction looks bright, and fast convergence
algorithms are sure to play a key role in creating a quieter, more peaceful world for us all.
• In this research, a time-frequency domain combined algorithm is proposed for active control of round noise.
On one hand, this algorithm implements FxLMS in frequency domain to obtain a good algorithm performance
at an extremely low computational cost.

8. Reference
• Elliott, S. J., Nelson, P. A., IEEE Signal Processing Magazine, 10-4, pp. 12-35 (1993).
• Haykin, S., Modern Filters, New York: Macmillan, 1989, ch. 6-8.
• Kuo, S. M., Morgan, D. R., Active Noise Control Systems: Algorithms and DSP Implementations, New York:
John Wiley & Sons, 1996, pp. 241-251.
• Cheer, J. and S. Elliott. Multichannel feedback control of interior road noise. in Proceedings of Meetings on
Acoustics ICA2013. 2013: ASA.
• Schirmacher, R., R. Kunkel and M. Burghardt, Active Noise Control for the 4.0 TFSI with Cylinder on
Demand Technology in Audi's S-Series. 2012, SAE International.