• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.8 s.251
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• pp.897-905
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• 2006

This study considers an experimental design of disturbance compensation control to improve stabilization performance of main battle tanks. An adaptive non-parametric design technique based on the Filtered-x Least Mean Square(FXLMS) algorithm is applied in the consideration of model uncertainties. The optimal compensator is designed by two-step design procedures: determination of frequency response function of the disturbance compensator which can cancel the disturbance of series of single harmonics by using the FXLMS algorithm and determination of the compensator polynomial which can fit the frequency response function obtained in the first step optimally by using a curve fitting technique. The disturbance compensator is applied to a simple experimental gun-torsion bar-motor system which simulates gun driving servo-system. Along with experimental results, the feasibility of the proposed technique is illustrated. Experimental results demonstrate that the proposed control reduces the standard deviation of stabilization error to 47.6% that by feedback control alone. The directional properties of the FXLMS Algorithm such as the direction of convergence and its convergence speed are also verified experimentally.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.489-496
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• 2008

This paper investigates active noise control of ducts using Filtered-x Least Mean Square (FXLMS) algorithms to reduce noise transmission. Single channel FXLMS (MFXLSM) and multiple channel FXLMS (MFXLMS) algorithms are used to implement the active control systems. The transmission loss is significantly increased by SFXLMS but the sound pressure level (SPL) at the upstream of the error sensor is increased while that of downstream is very low. This increase of the upstream SPL causes the duct wall to vibrate and so to radiate noise. To prevent the wall vibration generated by the sound field upstream, global sound field control is required. To reduce SPL globally along the duct, active noise control using MFXLMS is implemented. We can then obtained globally reduced SPL. It is found experimentally that the vibration level, and so the radiated noise level. can be reduced by the active noise control using MFXLMS.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.1
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• pp.24-34
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• 2009

This paper investigates active noise control of ducts using filtered-x least mean square(FXLMS) algorithms to reduce noise transmission. Single channel FXLMS(SFXLSM) and multiple channel FXLMS(MFXLMS) algorithms are used to implement the active control systems. The transmission loss is significantly increased by SFXLMS but the sound pressure level(SPL) at the upstream of the error sensor is increased while that of downstream is very low. This increase of the upstream SPL causes the duct wall to vibrate and so to radiate noise. To prevent the wall vibration generated by the sound field upstream, global sound field control is required. To reduce SPL globally along the duct, active noise control using MFXLMS is implemented. We can then be obtained globally reduced SPL. It is found experimentally that the vibration level, and so the radiated noise level, can be reduced by the active noise control using MFXLMS.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.22-25
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• 2004

In active noise control (ANC) system, the convergence behavior of the Filtered- X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortion in the secondary path as in the power amplifiers (e.g., saturation), loudspeakers and transducers. This distortion may yields degrading the error reduction performance of the ANC systems. In this paper, the authors of this paper propose a more improved and stable FXLMS algorithm to compensate for the undesirable nonlinearity of the secondary-path, whereby the third-order Volterra model was employed for the identification of the nonlinear secondary-path. In particular, the proposed approach was based on the modification of the conventional FXLMS algorithm. Finally, the simulation results showed that the proposed approach yields better convergence property and more stable performance in the ANC systems.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.27 no.1
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• pp.87-93
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• 2017

This paper investigates active noise control of tower-type air conditioners using the filtered-x least mean square (FXLMS) algorithm to reduce fan blower noise transmission. Firstly, the main components required for the active control system including the error sensor, the control speaker and the reference sensors are selected. Since the noise could significantly reduce if the reference signal includes every frequency response information, a various reference signals from accelerometers and a microphone are used. Secondly, the controller based on the FXLMS algorithm with a single-channel reference signal is implemented. Then, the control performance is examined experimentally for the different reference signals. It is found that the accelerometer signal well possesses the motor vibration related noise and a microphone signal could includes global noise. When using the reference signal with a microphone located near the motor and the fan blower, the active control system reduces the noise globally, except for several peaks.

• Journal of Power System Engineering
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• v.14 no.5
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• pp.56-62
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• 2010

In this paper, a recurrent cerebellar modulation articulation control (RCMAC) has been developed for improvement of noise attenuation performance in active noise control system. For the narrow band noise, a filter-x least mean square (FXLMS) method has bee frequently employed as an algorithm for active noise control (ANC) and has a partial satisfactory noise attenuation performance. However, noise attenuation performance of an ANC system with FXLMS method is poor for broad band noise and nonlinear path since it has linear filtering structure. Thus, an ANC system using RCMAC is proposed to improve this problem. Some simulations in duct system using harmonic motor noise and KTX cabin noise as a noise source were executed. It is shown that satisfactory noise attenuation performance can be obtained.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.18 no.3
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• pp.284-292
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• 2008

The active control technique mostly uses the least-mean-square(LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS(FXLMS) algorithm is applied to an active noise control(ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation and experimental results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.598-603
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• 2007

The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time, particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, FXLMS algorithm has the demerit that stability of the control is decreased when the step size become larger but the convergence speed is faster because the step size of FXLMS algorithm is fixed. As a result, the system has higher probability which the divergence occurs. Thus the Co-FXLMS algorithm was developed to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing the noise in duct system.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.184.1-184.1
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• 2005

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.737-742
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• 2007

The method of the reducing duct noise can be classified by passive and active control techniques. However, passive control has a limited effect of noise reduction at low frequencies (below 500Hz) and is limited by the space. On the other hand, active control can overcome these passive control limitations. The active control technique mostly uses the Least-Mean-Square (LMS) algorithm, because the LMS algorithm can easily obtain the complex transfer function in real-time particularly when the Filtered-X LMS (FXLMS) algorithm is applied to an active noise control (ANC) system. However, the convergence performance of the LMS algorithm decreases slightly so it may delay the convergence time when the FXLMS algorithm is applied to the active control of duct noise. Thus the Co-FXLMS algorithm was developed to improve the control performance in order to solve this problem. The Co-FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Co-FXLMS algorithm is presented in comparison with the FXLMS algorithm. Simulation results show that active noise control using Co-FXLMS is effective in reducing duct noise.