Active control of nonlinear noise processes in a linear duct

Strauch, P.; Mulgrew, Bernie

doi:10.1109/78.709529

Cited by 121 publications

(49 citation statements)

References 21 publications

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“…Research has shown that the noise measured from a ventilation fan exhibit chaotic behaviour [28]. Three kinds of chaotic noises in the form of Logistic, Lorenz, and Duffing noise filters have been applied to test the capability of a proposed single channel nonlinear controller [29]. The results from this study show that if the input signal is non-Gaussian and predictable, the use of a combination of linear and nonlinear controller produces better results than a linear one exclusively.…”

Section: Reference Noisementioning

confidence: 77%

Comparison of Performance and Computational Complexity of Nonlinear Active Noise Control Algorithms

Sahib

Kamil

2011

ISRN Mechanical Engineering

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Research on nonlinear active noise control (NANC) revolves around the investigation of the sources of nonlinearity as well as the performance and computational load of the nonlinear algorithms. The nonlinear sources could originate from the noise process, primary and secondary propagation paths, and actuators consisting of loudspeaker, microphone or amplifier. Several NANCs including Volterra filtered-x least mean square (VFXLMS), bilinear filtered-x least mean square (BFXLMS), and filtereds least mean square (FSLMS) have been utilized to overcome these nonlinearities effects. However, the relative performance and computational complexities of these algorithm in comparison to FXLMS algorithm have not been carefully studied. In this paper, systematic comparisons of the FXLMS against the nonlinear algorithms are evaluated in overcoming various nonlinearity sources. The evaluation of the algorithms performance is standardized in terms of the normalized mean square error while the computational complexity is calculated based on the number of multiplications and additions in a single iteration. Computer simulations show that the performance of the FXLMS is more than 80% of the most effective nonlinear algorithm for each type of nonlinearity sources at the fraction of computational load. The simulation results also suggest that it is more advantageous to use FXLMS for practical implementation of NANC.

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Section: Reference Noisementioning

confidence: 77%

Comparison of Performance and Computational Complexity of Nonlinear Active Noise Control Algorithms

Sahib

Kamil

2011

ISRN Mechanical Engineering

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“…This last result is especially important for ANC because several noise mechanisms have shown to exhibit chaotic behaviour [15], [16].…”

Section: Introductionmentioning

confidence: 97%

System Modeling for Active Noise Control with Reservoir Computing

Nyman¹,

Caluwaerts²,

Waegeman³

et al. 2012

Signal Processing, Pattern Recognition and Applications / 779: Computer Graphics and Imaging

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Abstract-This paper investigates the use of reservoir computing for active noise control (ANC). It is shown that the ANC problem can be solved by a concatenation of physically present subsystems. These subsystems can be modelled by reservoirs that are trained, using one shot learning. This approach is compared to genetic algorithms tuning a Volterra filter. Experimental results show that our approach works well as system model, meaning that a reservoir trained on white noise performs good on other input signals as well. This is a major advantage over genetic algorithms that generalize rather badly. Furthermore, our approach needs less data and this data can be gathered in one experiment only.

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“…The performance of linear ANC system would be degraded under this situation, so that nonlinear active controllers might be required in cases where the actuators used in ANC systems exhibit nonlinear characteristics (Strauch and Mulgrew, 1998, Bouchard et al, 1999, Efe and Kaynak, 2000, Tan and Jiang, 2001). …”

Section: Air Ductsmentioning

confidence: 99%

“…However, the consistency and predictability of the system cannot be clearly demonstrated by using this nonlinear NN controller. A combined linear and nonlinear model was implemented for active nonlinear noise control in a linear duct (Strauch and Mulgrew, 1998). The controller exploits the predictability of the input signal to eliminate the effects of using a nonminimum phase actuator as secondary path.…”

Section: Nonlinearitiesmentioning

confidence: 99%

Active control of pressure pulsation in a switched inertance hydraulic system

Pan

Johnston

Hillis

2013

Proceedings of the Institution of Mechanical Engineers, Part I:

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The nature of digital hydraulic systems may cause pressure pulsation problems. For example, switched inertance hydraulic systems (SIHS), which are applied to adjust or control flow and pressure by a means that does not rely on dissipation of power, have noise problems due to the pulsed nature of the flow. An effective method to reduce the pulsation is important to improve system performance and increase efficiency. Although passive systems to reduce the noise have been shown to be effective in many situations, their attenuation frequency range is limited and they may be bulky. Furthermore, attenuation devices based on expansion chambers, accumulators or hoses are likely to be unsuitable for SIHS as they add compliance to the system and would impair the dynamic response. This thesis is concerned with issues relating to the development of an active noise canceller for attenuating the pressure pulsation which is caused primarily by pulsed flow from high-speed valves in SIHS.Active control methods are widely and successfully applied in the area of structureborne noise (SBN) and air-borne noise (ABN) cancellation. The idea is using the intentional superposition of waves to create a destructive interference pattern such that a reduction of the unwanted noise occurs. However, applications for fluid-borne noise (FBN) attenuation based on the 'Active noise control (ANC) principle' are rare due to the restriction of the hardware and experimental apparatus in previous researches.In this thesis, an adaptive controller has been developed for active control of pressure pulsation in hydraulic system. The principle of the adaptive LMS filter and details of the controller design are described and the implementation was carried out through simulation. The designed controller was applied on a vibration test rig initially prior to the hydraulic testing in order to investigate its advantages and limitations in practice.Extensive testing on a switched inertance hydraulic rig proved that the controller, which used a piezoelectric valve with fast response and good bandwidth, is effective and that it has several advantages over previous methods, being effective for low frequency cancellation, with a quick response, and is robust and versatile. II A novel method for the accurate measurement of unsteady flowrate in a pipe was proposed. This was applied and validated on a pipe, and was shown to give good results. This method solves the difficulty for measuring the unsteady flowrate currently by using easy-measured signals, such as pressures. It can be used widely for predicting the unsteady flowrate along the pipe. III ACKNOWLEDGEMENTS

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Active control of nonlinear noise processes in a linear duct

Cited by 121 publications

References 21 publications

Comparison of Performance and Computational Complexity of Nonlinear Active Noise Control Algorithms

Comparison of Performance and Computational Complexity of Nonlinear Active Noise Control Algorithms

System Modeling for Active Noise Control with Reservoir Computing

Active control of pressure pulsation in a switched inertance hydraulic system

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