• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.12
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• pp.827-833
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• 2004

In active noise control (ANC) systems, the error-reduction performance of the conventional Filtered-X Least Mean Square (FXLMS) algorithm may be affected by nonlinear distortions in the secondary path such as in the power amplifiers, loudspeakers and transducers. In this paper, a nonlinear FXLMS algorithm with high error-reduction performance is proposed to compensate for undesirable nonlinearities in the secondary-path of ANC systems by employing the inverse 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 nonlinearity compensation performance for the ANC systems with a nonlinear secondary path than the conventional FXLMS.

• 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.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.1048-1053
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• 2003

This paper proposed a MR(Magneto-rheological) seat damper for a commercial vehicle. After formulating the governing equation of motion, an appropriate size of damper is designed and manufactured. Following the equation of fie d-dependent damping force characteristics, a semi-active seat suspension installed with the proposed MR-damper is constructed and its dynamic model id established, Subsequently, vibration isolation performance of the semi-active suspension system is demonstrated by incorporating with a MRAC(Model referenced adaptive control) fer the MR Seat Damper

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.108-114
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• 2009

This paper proposes the new hybrid adaptive controller for fast response time and precision control of automation system which exist deadzone or non-linearity of system. The proposed system, which provides the improvement in terms of the control region in high speed and precision control, first used the fuzzy control method for fast response time and when the error reaches the preset value, used the PLL method designing PFD improved jitter for precision control. The new designed PFD improves the jitter noise and response characteristic without generating deadzone. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably improved performance in the position control of automation system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.727-734
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• 2014

Digital processing technologies are being studied in various areas of image compression, recognition and recovery. However, image deterioration still occurs due to the noises in the process of image acquisition, storage and transmission. Generally in the typical noises which are included in the images, there are Gaussian noise and the mixed noise where the Gaussian noise and impulse noise are overlapped and in order to remove these noises, various researches are being executed. In order to preserve the edge and effectively remove mixed noises, image recovery filter algorithm was suggested in this study which sets and processes the adaptive weight using the median values and average values after noise judgment. Additionally, existing methods were compared through simulations and PSNR(peak signal to noise ratio) was used as a judgment standard.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.4
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• pp.385-390
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• 2009

This paper presents a novel active noise control (ANC) system using least mean square (LMS) algorithm and neural network approach for decreasing acoustic noise signals inside high-speed trains. We construct a LMS framework as a nominal ANC system and additionally design an artificial single-layered perceptron model as an auxiliary ANC which is aimed to reduce real-time residuary noise due to its nonstationary and uncertain nature. Parameter vector of the hybrid ANC is determined through online estimation to realize an adaptive ANC configuration by means of the steepest descent algorithm. We achieve simulation experiment to demonstrate the proposed ANC system employing realistic acoustic noise signals measured in Korea Train eXpress (KTX).

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.260-265
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• 2014

Recently, many active noise control (ANC) systems, which employ the adaptive filter controlling method, have been reported for eliminating unwanted noise. ANC systems based on the filtered-X least mean square (FXLMS) algorithm have a problem with compensating the acoustic feedback of secondary route. It is difficult to apply the real time, because transfer function of secondary route must be measured by off-line method to solve this problem. In this paper, we propose the ANC system that applies a correlation LMS(CLMS) algorithm for improving a problem of transfer function measurement. The proposed algorithm is based on input of road noise. The proposed ANC systems have an advantage of real-time process without degradation of performance, although there are many calculation compared with FXLMS algorithm.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.5
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• pp.303-309
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• 2016

This paper presents a channel-adaptive rate control algorithm for low delay video coding. The main goal of the proposed method is to adaptively use the unknown available channel bandwidth while reducing the end-to-end delay between encoder and decoder. The key idea of the proposed algorithm is for the status of the encoder buffer to indirectly reflect the mismatch between the available channel bandwidth and the generated bitrate. Hence, the proposed method fully utilizes the unknown available channel bandwidth by monitoring the encoder buffer status. Simulation results show that although the target bitrate mismatches the available channel bandwidth, the encoder efficiently adapts the given available bandwidth to improve the peak signal-to-noise ratio.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.5
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• pp.311-318
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• 1988

An adaptive control problem for a plant with unmodelled dynamics is studied. The upper bounds of the output due to the unmodelled dynamics and measurement noise is assumed to be known. This problem was studied by Middleton et al. They used a modified form of the least square method in estimating the plant paramaters. In this paper, the bounds of the parameters are estimated by linear programming and the parameters are estimated by the projetion type algorithm incorporating the bounds of the parameters. The stability of the proposed adaptive control system can be proved in nearly the same way as the proof of Middleton. The performance of the proposed method is found to be much better than the method of Midlleton's with respect to the parameter convergence and plant output in computer simulations.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.285-290
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• 2006

This paper presents an adaptive neural network based controller and its application to Dynamic Positioning (DP) control system of ship. The proposed neural network based controller is developed for station-keeping and low-speed maneuvering control of ship. At first, the DP system configuration is described. And then, to validate the proposed DP system, computer simulations of station-keeping and low-speed maneuvering performance of a multi-purpose supply ship are presented under the influence of measurement noise, external disturbances such as sea current, wave, and wind. The simulations have shown the feasibility of the DP system in various maneuvering situations.