• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.10a
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• pp.357-363
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• 2009

This paper deals with the Filtered-x Least Mean Square algorithm for a active vibration control in vehicle vibration reduction. Before applying the proposed FxLMS algorithm to automobile, the performance of the FxLMS algorithm is simulated using sensor data of a vehicle. The FxLMS algorithm requires that reference signal be a representation of disturbance signal and the plant model be incorporated into the computation path. To this end, The system identification is carried out to obtain the plant model based on the measurement results. A tachometer signal is used as reference signal. The FxLMS control algorithm is first tested using simulation and applied to a vehicle. Experimental results show that the proposed control algorithm can reduce vibration level in a short period of time.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.570-575
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• 2019

Active muffler is implemented by applying active noise control technique to reduce exhaust noise of automobile muffler. Conventional Filtered_x LMS algorithm has a problem that the degree of control filter becomes very large and convergence deteriorates when acoustic feedback is present. The recursive LMS algorithm can compensate for this problem because it can be easily diverted in the adaptive filter adaptation process. In this paper, the structure of the primary path and the secondary path transfer function is designed as the IIR filter to improve the convergence performance and the computational burden, and the stabilization filter algorithm is applied to secure stability which is a disadvantage of the IIR filter structure. The stabilization filter algorithm plays a role of pulling the pole into the unit circle to prevent the pole of the transfer function corresponding to the acoustic feedback from diverging during the adaptation process. In this way, the computational burden of the active muffler system and the convergence performance can be improved. In order to show the usefulness of the proposed system, we compared the performance of the proposed Filtered_x LMS algorithm with the performance of the proposed system for the exhaust sound of a diesel engine, which is a variable environment. Compared to conventional algorithm, proposed algorithm's computational burden is less than half, and convergence performances are more than 4 times.

• The Journal of the Acoustical Society of Korea
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• v.34 no.2
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• pp.130-137
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• 2015

In this paper, we propose a new Modified Filtered-x Affine Projection Sign Algorithm(MFxAPSA) to improve the convergence speed of the conventional MFxAPSA which has been proposed for active control of impulsive noise. Under the impulsive noise environment, the adaptive algorithms based on the second order moment such as the Filtered-x Least Mean Square(FxLMS) show slow convergence speed or diverge because the noise source tends to have infinite variance. The MFxAPSA is the algorithm derived by applying the Affine Projection Sign Algorithm(APSA) to active noise control. The APSA has an advantage that it does not need the calculation for the inverse matrix, so it may be suitable for the active noise control that requires low computational burden. The proposed MFxAPSA also has APSA's advantage and furthermore, better performance than the conventional MFxAPSA. We carried out a performance comparison of the proposed MFxAPSA with the conventional MFxAPSA. It is shown that the proposed MFxAPSA has the faster convergence speed than the conventional MFxAPSA.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.1
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• pp.40-47
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• 2005

This paper concerns on Filtered-x least mean square (FXLMS) algorithm for adaptive estimation of feedforward control parameters. The conditions for convergence in ensemble mean of the FXLMS algorithm are derived and the directional convergence properties are discussed from a new geometric vector analysis. The convergence and its directionality are verified along with some computer simulations.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.3
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• pp.107-113
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• 1997

This paper presents the active control of a flexible cantilever beam vibration. The cantilever beam was excitied by a steady-state harmonic and white noise point force and the control was performed by one piezo ceramic actuator bonded to the surface of the beam. An adaptive controller based on filtered-x LMS algorithm was used and the controller was defined by minimizing the square of the response of error sensor. In the experiment, gap sensor was used as an error sensor while the sinusoidal or white noise was applied as a disturbance. In the case of sinusoidal input, more than 20 dB of vibration reduction was achieved over all range of the natural frequencies and it takes 5 seconds to control the vibration at first natural frequency and 1 second at other natural frequencies. In the case of white noise input, 7 dB of vibration reduction was achieved at the first natural frequency and good control performance was achieved in the considered whole frequency range. Results indicate that the vibration of a flexible cantilever beam could be controlled effectively when the piezo ceramic actuator was used with filtered-x LMS algorithm.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.65 no.3
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• pp.171-177
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• 2016

Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.

• Journal of KSNVE
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• v.2 no.2
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• pp.107-116
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• 1992

An adaptive signal processing technique is implemented for the active noise cancellation of the plane acoustic wave propagating in a duct. To avoid the instability caused by the acoustic feedback from the control speaker to the detect microphone, an off-line modeling of the acoustic feedback plant is done using the FIR filter. Auxiliary path required for the filtered-x LMS algorithm is modeled as well. Before going into the experiments, a simulation is carried out under the same conditions with experiments. The simulation shows that the longer the length of the adaptive filter is, the better the results are achieved. Experiments have been carried out at lower audio frequency range (50 - 400Hz), and the results are in good agreements with those of simulation study. As a results of this adaptive noise control, around 50dB is reduced for a pure tone noise, and for a bandlimited noise with the bandwidth of 316Hz, a maximum of 30dB noise reduction is attained.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.57-63
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• 2017

This paper presents an active acoustic-reflection control algorithm based on a single sensor. The proposed algorithm operates in a system comprising a single sensor located nearby the reflective surface and a control transducer mounted on the reflective surface. First, the incident and reflected acoustic signals are separated from the sensor signal, and a control signal is generated using the separated signals. For the signal separation, the proposed algorithm requires the response of the reflection path which is estimated from the acoustic response between an external sound source and the sensor. Finally, the control filter is adjusted using the FxLMS (Filtered-x Least Mean Square) algorithm. To verify the effectiveness of the proposed algorithm, it was implemented in real time using a DSP (Digital Signal Processing) board, and the experimental results obtained in one-dimensional air-acoustic environment show that the reflections of the 1 kHz burst can be reduced by 11.6 dB.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.5
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• pp.34-40
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• 2001

In this paper, a narrowband active noise control system to reduce the noise in thermal power plants is proposed. The narrowband active noise control system contains rectangular wave generator and has a multi channel feed forward adaptive algorithms which uses the adjoint LMS algorithm. Although the effectiveness have been proven in the filtered-X LMS broadband active noise control system, this algorithm has much more computational complexity than that of narrowband active noise control system. The proposed active control system that uses the adjoint LMS algorithm, compared to the previous broadband active noise control system, not only is more effective in controlling narrowband noise but also has a more stable structure. Adaptive filter contains the FIR structure and IIR structure for primary and secondary path models. The simulation proves the effectiveness of the proposed algorithm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.780-783
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• 2004

Recently Intake noise has been extensively studied to reduce the engine noise. In order to diminish intake noise several resonators were added to the intake system. However this can cause a reduction of engine output power and an increase of fuel consumption. In this study, active noise control simulation of the Filtered-x LMS algorithm is applied real instrumentation intake noise data under rapid acceleration because intake noise is more excessively increased under the such a harsh condition. But the FXLMS algorithm has poor control performance when the system is disturbed. Thus modified FXLMS algorithm using L-point running average filter is developed to improve the control performance under the rapid acceleration and disturbance. The noise reduction quantity of modified Filtered-x LMS algorithm is more than original one in two cases. In the case of control for real instrumentation intake noise data, maximum residual noise of modified FXLMS algorithm is 2.5 times less than applied the FXLMS and also in the case of disturbed, the modified FXLMS algorithm shows excellent control performance but FXLMS algorithm cat not control.