• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.4
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• pp.267-272
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• 2015

Active noise control (ANC) is a method of cancelling a noise signal in an acoustic cavity by generating an appropriate anti-noise signal via canceling loudspeakers. The continuous progress of ANC involves the development of improved adaptive signal processing algorithms, transducers, and DSP hardware. In this paper, the convergence behavior and the stability of the FxLMS algorithm in ANC systems with real-time implementation is proposed. Specially, The advanced DSP H/W with dual core(DSP+ARM) and API(application programming interface) S/W programming was developed to improve the real-time implementation performance under the FxLMS algorithms of input noise such as road noise environment. The experimental results are found to be in good agreement with the theoretical predictions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.17-22
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• 2005

This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection c! the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances are presented.

• Journal of Navigation and Port Research
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• v.29 no.9
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• pp.771-776
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• 2005

This paper presents a new adaptive autopilot for ships based on the Adaptive Neural Networks. The proposed adaptive autopilot is designed with some modifications and improvements from the previous studies on Adaptive Neural Networks by Adaptive Interaction (ANNAI) theory to perform course-keeping, turning and track-keeping control. A strategy for automatic selection of the neural network controller parameters is introduced to improve the adaptation ability and the robustness of new ANNAI autopilot. In Part II of the paper, to show the effectiveness and feasibility of the proposed ANNAI autopilot, computer simulations of course-keeping and track-keeping tasks with and without the effects of measurement noise and external disturbances will be presented.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.31-36
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• 2009

This paper presents a novel scalar adaptive filter, which is reformulated by additional acceleration term. The filter continuously estimates three different kinds of covariance such as the measurement noise covariance, the velocity error covariance and the acceleration error covariance. For estimating three covariances, we use the innovation method for the measurement noise covariance and the least square method for other covariances. In order to verify the proposed filter performance compared with the conventional scalar adaptive filter, we make indoor experimental environment similar to outdoor test using the ultrasonic sensors instead of GPS. Experimental results show that the proposed filter has better position accuracy than the traditional scalar adaptive filter.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.137-142
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• 2005

Biomedical signals such as ECG, EMG, and EEG are extremely important in the diagnosis of patients. It is difficult to filter noise from these signals, and errors resulting from filtering can distort a biomedical signal. Existing systems have shown poor performance when complicated noise appears. Adaptive filtering is selected to contend with these defects. Existing adaptive filters can adjust the filter coefficient with the given filter order, but they can produce an unsuitable order in different environments. In order to solve this problem, an optimal adaptive filter with a dynamic structure was designed. Positive experimental results were obtained.

• Journal of KSNVE
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• v.8 no.5
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• pp.832-840
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• 1998

Experimental studies on the adaptive vibration control of composite beams have been performed using a piezoelectric actuator and the neuro-controller. The variations in natural frequencies of the specimen and the actuation characteristics of the piezoelectric actuator according to the delamination in the bonding layer have been studied. In addition, the simulation of adaptive vibration control has been performed for the composite specimens with delaminated piezoelectric actuator using neuro-controller. The hardware for the adaptive vibration control experiment was prepared. A DSP(digital signal processor) has been used as a digital controller. Using neuro-controller, the adaptive vibration control experiment has been performed. The vibration control results using the neuro-controller show that the present neuro-controller has good performance and robustness with the system parameter variations.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.431-436
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• 2000

Adaptive feed forward control algorithms based largely upon LMS approach have developed in recent two decades, and they have been widely applied to practical sound and vibration control problems in the case of the reference signal is available. Feedforward control can be applied only when reference signals can be measured or regenerated, while feedback controllers are used to reduce; sound and vibration when reference signals are not available. In recent years, hybrid control schemes in which adaptive feed forward controllers are combined with feedback ones have been studied based on simulations and experiments. The results have shown that the hybrid control may have better control performances in convergence speed and steady state error than the single control schemes. Hybrid control has the advantages of improving stability and performance as well as the disturbance rejection property. However, little effort has been made to the analysis or interpretation of hybrid control systems. In this study, we discussed the feedback controller effects on the stability of feed forward control algorithm in the presence of uncertain error path and a simple example showed that a stable feedback controller could make the feedforward controller unstable. A design criterion of feedback controllers is proposed in order to guarantee the stability of feedforward algorithms in the presence of error paths with uncertainties.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.11
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• pp.1837-1843
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• 1997

This study experimentally demonstrates the use of active muffler attached to the automotive exhaust system to reduce exhaust noise. For improving the signal to noise ratio in the process of estimation of secondary path transfer functions, the on-line algorithm that conventional inverse modeling is combined with adaptive line enhancer is used as the control algorithm. Active muffler is designed that the primary noise and the control sound are propagated as a plane wave in the outlet. Therefore, the error microphone could be placed out of the tail pipe center of a high temperature and the radiation noise to the outside could be reduced in the whole area around the outlet. The control experiment for reducing exhaust noise with active muffler is implemented during run-up at no load. From the experimental results presented, compared with the conventional off-line method, the proposed on-line method is capable to acquire a reduction of exhaust noise above 5 dB in overall sound power level.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.15-23
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• 1994

This paper described adaptive ANC (Active Noise Control) systems for noise canacelling in multiple inputs and multiple outputs channel. Until this time, it was reported that the study of AMC for the multiple inputs and the multiple outputs had no correlation between input signals of adaptive filters. In fact, it is difficult independently to check the noise source signals and insufficient about this study. In this paper we proposed to use the adaptive filter for eliminating the correlation between input signals. The simulation results showed that the convergence rate improved about two times with this filter than that one without this filter at the rate $b_{12}=0.95$.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.903-905
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• 2015

The need for digital devices is increasing in the digital age. In general, noise in images occurs during the process of compression, recognition and processing due to many reasons. Some of the filters used to remove salt and pepper noise include SMF, CWMF and AMF. In areas where the noise density is high, the removal of noise is undermined. This paper suggests an adjusted median filter algorithm that preserves the non-noise pixels while transforming the noise pixels to more effectively remove salt and pepper noise.