• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.4
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• pp.239-246
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• 2003

Application of the filtered-x Least Mean Square(LMS) adaptive filter to active noise control requires to estimate the transfer characteristics between the output and the error signal of the adaptive controller. In this paper, we derive the filtered-x adaptive noise control algorithm and analyze its convergence behavior when the acoustic noise consists of multiple sinusoids. The results of the convergence analysis of the filtered-x LMS algorithm indicate that the effects of the parameter estimation inaccuracy on the convergence behavior of the algorithm are characterized by two distinct components Phase estimation error and estimated gain. In particular, the convergence is shown to be strongly affected by the accuracy of the phase response estimate. Simulation results are presented to support the theoretical convergence analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2120-2125
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• 2005

The principal idea of vibration isolation is to filter out the response of the system over the corner frequency. The isolation objectives are to transmit the attitude control torque within the bandwidth of the attitude control system and to filter all the high frequency components coming from vibration equipment above the bandwidth. However, when a reaction wheels or control momentum gyros control spacecraft attitude, vibration inevitably occurs and degrades the performance of sensitive devices. Therefore, vibration should be controlled or isolated for missions such as Earth observing, broadcasting and telecommunication between antenna and ground stations. For space applications, technicians designing controller have to consider a periodic vibration and disturbance to ensure system performance and robustness completing various missions. In general, past research isolating vibration commonly used 6 degree order freedom isolators such as Stewart and Mallock platforms. In this study, the vibration isolation device has 3 degree order freedom, one translational and two rotational motions. The origin of the coordinate is located at the center-of-gravity of the upper plane. In this paper, adaptive notch filter finds the disturbance frequency and the reference signal in filtered-x least mean square is generated by the notch frequency. The design parameters of the notch filter are updated continuously using recursive least square algorithm. Therefore, the adaptive filtered-x least mean square algorithm is applied to the vibration suppressing experiment without reference sensor. This paper shows the experimental results of an active vibration control using an adaptive filtered-x least mean squares algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.3
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• pp.197-205
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• 2014

In applications of adaptive noise control or active noise control, the presence of a transfer function in the secondary path following the adaptive controller and the error path, been shown to generally degrade the performance of the Least Mean Square (LMS) algorithm. Thus, the convergence rate is lowered, the residual power is increased, and the algorithm can become unstable. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used. But these algorithms have slow convergence speed and weakness in the environment that the secondary path and error path are varied. Therefore, I present the new algorithm called the "Bi-directional Filtered-x (BFX) LMS" algorithm with nearly equal computation complexity. Through experimental study, the proposed BFX-LMS algorithm has better convergence speed and better performance than the conventional FX-LMS algorithm, especially when the secondary path or error path is varied and the impulsive disturbance is flow in.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.4
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• pp.133-142
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• 2014

The least mean square(LMS) algorithm has been popular owing to its simplicity, stability, and availability to implement. But it inherently has a problem of slow convergence speed, and the presence of a transfer function in the secondary path following the adaptive controller and the error path has been shown to generally degrade the stability and the performance of the LMS algorithm in applications of acoustical noise control. In general, in order to solve these problems, the filtered-x LMS (FX-LMS) type algorithms can be used and the bi-directional Filtered-x LMS(BFXLMS) algorithm is very attractive among them, which increase the convergence speed and the performance of the controller with nearly equivalent computation complexity. In this paper, a mathematical analysis for the BFXLMS algorithm is presented. In terms of view points of time domain, frequency domain, and stochastic domain, the characteristics and stabilities of algorithm is accurately analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.11
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• pp.100-107
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• 2003

This paper represents a disturbance compensation control for attenuating disturbance responses. In the consideration of the requirements on the model accuracy in the model based compensator designs, an experimental feed forward compensator design based on adaptive estimation by Filtered-x least mean square (FXLMS) algorithm is proposed. The convergence properties of the FXLMS algorithm are discussed and its conditions for the asymptotic convergence are derived theoretically. The effectiveness of the proposed method and the theoretical proof are verified by computer simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.447-450
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• 2003

This paper concerns on application of active magnetic bearing(AMB) system to levitate the elevation axis of an electro-optical sight mounted on moving vehicles. In such a system. it is desirable to retain the elevation axis within the predetermined air-gap while the vehicle is moving. A disturbance compensation control is proposed to reduce the base motion response. In the consideration of the uncertainty of the system model, a filtered-x least-mean-square(FXLMS) algorithm is used to estimate adaptively the frequency response function of the feedforward control which cancels disturbance responses. The frequency response function is fitted to an optimal feedforward control. Experimental results demonstrate that the proposed control reduces the air-gap deviation to 27.7% that by feedback control alone.

• The Journal of the Acoustical Society of Korea
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• v.35 no.4
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• pp.280-287
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• 2016

In this paper, we propose a normalization algorithm that can be applied to adaptive filters for multi-channel active noise control. The FxLMS (Filtered-x Least Mean Square) algorithm for the single-channel active noise control can be normalized in the same way as the NLMS (Normalized Least Mean Square) algorithm, whereas in case of the multi-channel active noise control, the single-channel normalization for the FxLMS algorithm cannot be extended to the normalization for the multi-channel FxLMS algorithm straightforwardly. First, we adopt a generalized normalization algorithm for the multi-channel FxLMS algorithm based on the principle of minimal disturbance and then, proposed a normalized algorithm considering only diagonal elements to avoid computation for matrix inversion. We carried out performance comparisons of the proposed algorithm with other algorithms without normalization. It is shown that the proposed algorithm presents better convergence characteristics under non-stationary environments.

• 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.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.565-567
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• 2004

In active noise control (ANC) systems, the convergence behavior of the conventional Filtered-X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortions in the secondary path (e.g., in the power amplifiers, loudspeakers, transducers, etc.), which may lead to degradation of the error-reduction performance of the ANC systems. In this paper, a stable FXLMS algorithm with fast convergence is proposed to compensate for undesirable nonlinear distortions in the secondary-path of ANC systems by employing the Volterra filtering approach. In particular, the proposed approach is based on the utilization of the conventional P-th order inverse approach to nonlinearity compensation in the secondary path of ANC systems. Finally, the simulation results showed that the proposed approach yields a better convergence behavior In the nonlinear ANC systems than the conventional FXLMS.

• The Journal of the Acoustical Society of Korea
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• v.19 no.2E
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• pp.3-7
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• 2000

Vibration generated by the non-uniform road profile propagates though each tire and the suspension and finally generates structure born noise in the interior of the passenger vehicle. In this paper, the road-booming-noise which has strong correlation with the vibration signals measured at the suspension system was compensated. Active noise control of the road-booming-noise is rather difficult to achieve because of its non-stationary characteristics. CMFX LMS (Constraint Multiple Filtered-X Least Mean Square) algorithm, which can track non-stationary process rather well, is applied. Comprison of the proposed method and the conventional MFX LMS (Multiple Filtered-X Least Mean Square) algorithm is made through the hardware-in-the-loop simulation and the feasibility of the proposed method is demonstrated with the experiment.