• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1618-1624
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• 1988

In this paper, a robust discrete model reference adaptive controller is proposed using a generalized model reference adaptive algorithm for single-input single-output discrete systems. A signal dependent time-varying dead-zone is employed in a generalized adaptive control structure. This adaptive controller is shown to assure the boundedness of the signals of the system even in the presence of bounded external disturbance.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1610-1617
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• 1988

In this paper, a robust discrete-time adaptive control with compensation is proposed for single-input single-output discrete-time plants which have unmodeled dynamics. The stability of the overall system is studied using the conic sector stability theorems when a normalized constant gain parameter adaptation algorithm and a properly chosen compensation are used. An illustrative exmple shows that this compensation can also increase the parameter adaptation speed. And a method of compensation using the adaptive observation is also discussed.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2593-2596
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• 2003

The deadbeat properties have been well known in designing digital control systems. But recently several researchers proposed a CDBC(Continuout-time DeadBeat Controller) in continuous time. They used delay or smoothing elements from the finite Laplace Transform. A delay element is made by the exponential terms. A smoothing element is used to smooth the digital control input. And eventually the process is argumentd with smoothing elements and then well-known digital deadbeat controller is designed Sometimes samplings are done in continuous time systems and some hold devices are used to relate to digital systems. So multirate sampling may enhance the efficiency of the CDBC. A DC servo motor is chosen for implementing CDBC algorithm. Especially Outputs according to the variable input and disturbance are simulated. by use of Matlab Simulink.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.1-8
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• 1994

There are many research activities in various recognition areas using high calibered computing power. Among many areas, the signature recognition and verification have more difficulties than any other recognition area because signature itself contains many problems caused by a variation of psychological status of signer and other environment. In the case of signature, therefore, it is important to extract the better parameters required for the higher verification ratio. In this paper, signature pressure is extracted and used as feature parameters to determine whether the input signature is ture or forgery, and then input signature is verified by fuzzy similarity method. As a result of appling the fuzzy similarity method to the recognition system it is proven that the system has by far better verification ratio about 10% than existing methods.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.1
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• pp.57-63
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• 1994

The logic function synthesis using ULM U$_h$ is constructed based on canonic Reed-Muller expansion coefficient for a given function. This paper proposes the fast synthesis algorithm using ULM U$_h$ for ternary function. By using circuit cost and synthesis method of proposed in this paper, order of control input variable minimum number of ULM U$_h$ can be decided in the synthesis of n-variable ternary function. Accordingly, this method enables to optimum circuit realization for ternary function synthesis using ULM ULM U$_h$ and can be applied to ternary function synthesis using ULM U$_h$. The complexity of search for select the order of all control input variables is (n+2)(n-1)/2.

• 전자공학회논문지 IE
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• v.44 no.3
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• pp.51-55
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• 2007

In this paper, we consider the controllability and observability for the time-varying linear system using the input-state(I/O), input-output(I/O) transformation and get the time-invarying linear system. The transformed system represent the system with the multiple integral. We verify the proposal algorithm via the example and examine.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.503-506
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• 2001

In this paper, we describe the implementation of a microphone input level control algorithm and the speech improvement with this level controller in personal computer environment. The volume of speech obtained through a microphone affects the speech recognition rate directly. Therefore, proper input volume level control is desired fur better recognition. We considered some conditions for the successful volume controller implementation firstly, then checked its usefulness on our speech recognition system with common office environment speech database. Cepstral mean subtraction is also utilized far the channel-effect compensation of the database. Our implemented controller achieved approximately 50% reduction, i.e., improvement in speech recognition error rate.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.553-556
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• 2000

This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.

• Tribology and Lubricants
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• v.16 no.6
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• pp.461-468
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• 2000

In this study, a neural network based diagnostic system of a rotating spindle system supported by ball bearings was introduced. In order to create actual failure situations, two exemplary abnormal status were made. Out of several possible data source locations, ten measurement spots were chosen. In order to discriminate multiple abnormal status, a neural network system was introduced using back propagation algorithm updating connecting weight between each nodes. In order to find the optimal structure of the neural network system reducing the information sources, magnitude of the weight of the network was referred. Hinton diagram was used to visually inspect the least sensitive weight connecting between input and hidden layers. Number of input node was reduced from 10 to 7 and prediction rate was increased to 100%.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.2
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.