• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.267-271
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• 1996

In this study, performance improvement of the inverse modeling as the on-line control method for the estimation, control experiment is performed. As the modeling errors is occurred in duct system arbitrarily, a case using the filtered-x LMS algorithm only as the control method, a case using tile inverse modeling method only and a case using the inverse modeling with the adaptive line enhancer are compared. The estimation errors between real secondary path transfer functions and the estimated and the control performances of primary noises with these estimated transfer functions are compared.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.2
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• pp.281-287
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• 1997

In the conventional inverse modeling method for on-line modeling of the secondary path transfer function, the signal to noise ratio between the arbitrary random signal and the plant noise have to keep at -10 - -20 dB. For these reasons, the modeling can't be exactly implemented by the conventional method alone and the convergence time for modeling becomes too long. In this study, by combining the conventional inverse modeling method with an adaptive line enhancer, or with an adaptive noise canceller, a rigorous transfer functions of secondary path modeling and the control of a primary noise have been implemented simultaneously.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.283-287
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• 1996

The exhaust noise reduction of automobile with the active muffler is experimentally investigated. The control algorithm is the filtered-x LMS algorithm and the inverse algorithm with the adaptive line enhancer. Also, the control efficiency is increased with synthesized second harmonic engine frequency. In the experiment, the active muffler is applied to the end of exhaust system in automobile and the control with on-line secondary path modeling method(inverse algorithm) is compared the control of off-line secondary path modeling method. As secondary path transfer functions are changed, the experimental results show that the control performance with on-line method is more efficient than that with off-line method in the exhaust noise reduction of automobile.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.243-246
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• 1994

In this paper, a self-learning fuzzy controller is designed with a fuzzy approximation of an inverse model. The aim of an identification is to find an input command which is control of a system output. It is intuitional and easy to use a classical adaptive inverse modeling method for the identification, but it is difficult and complex to implement it. This problem can be solved with a fuzzy approximation of an inverse modeling. The fuzzy logic effectively represents the complex phenomena of the real world. Also fuzzy system could be represented by the neural network that is useful for a learning structure. The rule of a fuzzy inverse model is modified by the gradient descent method. The goal is to be obtained that makes the design of fuzzy controller less complex, and then this self-learning fuzz controller can be used for nonlinear dynamic system. We have applied this scheme to a nonlinear Ball and Beam system.

• The Journal of the Acoustical Society of Korea
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• v.11 no.1E
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• pp.56-63
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• 1992

The poblem of active oise control has been analysed using a adaptive signal processing technique. In this methods, the adaptive signal processor or model predicts the primary sound wave travelling along the acoustic plant and generates the secondary source 180° out of phase which attempts to attempts to attenuate the undesired noise by destructive interference. In the solutions presented here, acoustic propagation delay is considered as a part of the model which used the FIR filter. The effects of error path and auxiliary path transfer functioin are anayzed and a new on=-line technique for error path modeling, adaptive delayed inverse modeling is presented. In this study, using these new concepts, our system can more reduce the noise level in duct to 5dB-15dB than only using LMS algorithm system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1274-1282
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• 1996

This paper deals with an inverse modeling of nonminimum phase communication channel utilizing the HOS (High Order Statistics) of the received signal. After the communication channel is separated into the minimum phase and maximum phase components, the inverse modeling is performed independently. The performance superiority is confirmed by monte-carlo computer simulation in comparison with the traditional CMA (Constant Modulus Algorithm) method. By utilizing the proposed algorithm employing the HOS of the received signal, the inverse frequency characteristics of the channel can be obtained withoug transmitted signal in digital communication. This algorithm is required in preprocessing or postprocessing in order to remove the channel effect, and effective in the self adaptive equalizer which can minimize the bit error rate or symbol error rate in the recovry of received signal.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.11
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1131-1138
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• 2003

Active noise control(ANC) is an approach to noise reduction in which a secondary noise source destructively interferes with the unwanted noise is introduced. Generally, the performance of ANC is determined how well a secondary noise tracks noises. A secondary noise is generated from the cancelling speaker and a error sensor pick up error signal. The transfer function between the cancelling speaker and the error sensor is not flat and distorts secondary noises. Consequently, the performance of ANC is degraded by the transfer function. In this paper, a single sensor ANC which considers the characteristics of the speaker and the error sensor is proposed. To reduce distortion of secondary noises, the transfer function is estimated by adaptive inverse modelling and the primary noises are estimated by Kalman filter. Experimental results show that the proposed single sensor ANC effectively attenuates noises.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1995.06a
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• pp.165-170
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• 1995

In this paper, it is attempted to apply the adaptive digital signal processing to compensate for a linear distortion of a loudspeaker and implement a real time hardware for that purpose. The real time system is implemented by using the DSP56001, a general purpose signal processor, as a host processor and the DSP56200, a cascadable adaptive FIR filter peripheral chip, as an adaptive digital filter. The system has 1000 taps at a 44.1kHz. After inverse modeling of under_compensation_speaker, the system reduces loudspeaker's linear distortions by pre-processing an input audio signal to loudspeaker. The experiment shows satisfactory results; after adaption with white noise as input signal for 60sec, the flat amplitude and linear phase frequency characteristics is found to lie over a wide frequency range of 100Hz to 20kHz.