• 한국지능시스템학회:학술대회논문집
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• 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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• pp.341-344
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• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• 전자공학회논문지S
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• 제36S권9호
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• pp.58-66
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• 1999

단 입력 단 출력 시스템의 출력을 포함한 궤한 선형화 문제는 Lee [5] 등에 의해서 해결이 되었다. 또한 Cheng [1]등이 다 입력 다 출력 비선형 시스템에 대한 필요 충분조건을 발견하였지만, 점검할 수 없는 조건이다. 본 논문에서는 다 입력 다 출력 비선형 시스템의 출력을 포함한 궤한 선형화의 점검 가능한 필요충분조건을 구한다.

• International Journal of Automotive Technology
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• 제7권2호
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• pp.179-185
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• 2006

Airbag deployment has been responsible for huge death, incidental injuries and broken bones due to low crash severity and wrong deployment decision. This misfortune has led the authorities and the industries to pursue uniquely designed airbags incorporating crash-sensing technologies. This paper provides a thorough discussion underlying crash sensing algorithm approaches for the subject matter. Unfortunately, most algorithms used for crash sensing still have some problems. They either deploy at low severity or fail to trigger the airbag on time. In this work, the crash-sensing algorithm is studied by analyzing the data obtained from the variables such as (i) change of velocity, (ii) speed of the vehicle and (iii) acceleration. The change of velocity is used to detect crash while speed of the vehicle provides relevant information for deployment decision. This paper also demonstrates crash severity with respect to the changing speed of the vehicle. Crash sensing simulations were carried out using Simulink, Stateflow, SimMechanics and Virtual Reality toolboxes. These toolboxes are also used to validate the results obtained from the simulated experiments of crash sensing, airbag deployment decision and its crash severity detection of the proposed system.

• Journal of Communications and Networks
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• 제8권2호
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• pp.169-174
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• 2006

In this paper, the algorithm of a methodology for the calculation of spectrum requirements was implemented. As well, the influence of traffic distribution ratio among radio access technology groups, spectral efficiency, and flexible spectrum usage (FSU) margin was analyzed in terms of the spectrum requirements, with a view toward for future development of international mobile telecommunication (IMT)-2000 and systems beyond IMT-2000. The calculated spectrum requirement in the maximum spectral efficiency case is reduced by approximately 40% compared to a minimum spectral efficiency case. The effect of the distribution ratio on the required spectrum is smaller than the effect of the spectral efficiency. As the flexible spectrum usage margin increases by 1.0 dB, the total spectrum requirement decreases by 0.9 dB. The required spectrum for the market input parameter, ${\rho}$ = 0.5 is 801.63 MHz, while the required spectrum for ${\rho}$ = 1.0 is 6295.4 MHz. This is equivalent to an increase of 785.32 %.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.621-623
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• 2000

In this paper, the effective design method of the predictive controller using fuzzy neural networks(FNNs) is presented for the Intelligent control of chaotic nonlinear systems. In our design method of controller, predictor parameters are tuned by the error value between the actual output of a chaotic nonlinear system and that of a fuzzy neural network model. And the parameters of predictive controller using fuzzy neural network are tuned by the gradient descent method which uses control error value between the actual output of a chaotic nonlinear system and the reference signal. In order to evaluate the performance of our controller, it is applied to the Duffing system which are the representative continuous-time chaotic nonlinear systems and the Henon system which are representative discrete-time chaotic nonlinear systems.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.525-525
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• 2000

In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

• 전기학회논문지
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• 제63권7호
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• pp.1019-1023
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• 2014

The issue of safety insurance in PES(Programmable Electronic Systems) has been provoked because PES is difficult to define failure modes which are appeared in many different ways. But the PES applications extend rapidly in various areas. One of the solutions for PES safety insurance is voting which PES is used by comparing the outputs of several PES. The time synchronization of the PES is necessary for this reliable voting. The voting must be carried out with the outputs from same time inputs. There are several methods for time synchronization of the PES. In this paper, we discussed two modes of the time synchronization which are mutual synchronization of several PES and using UTC(Universal Time Clock).

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• 제3B권4호
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• pp.195-201
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• 2003

In accordance with the computerization of railway signaling systems, the interface link between signaling equipment has been replaced by a digital communication channel and the importance of this communication link has become increasingly significant. However, there are some problems with the present state of railway signaling. First, different communication protocol is applied to interfaces between signaling although they have the same functions. Next, the communication protocols currently used in the railway fields contain various illogical components such as structure, byte formation, error correction scheme and so on. To solve these matters, a new data link protocol for railway signaling systems is designed. In this paper, the structure of protocol and the results of performance analyses are presented. It will be expected to increase the safety, reliability and efficiency of maintenance of signaling systems by using the designed communication protocol for railway signaling in Korea.

• Journal of Electrical Engineering and Technology
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• 제4권1호
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• pp.135-142
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• 2009

In this paper the Simplified Refined Instrumental Variable (SRIV) identification algorithm for SISO systems is extended to MIMO systems described by a Left Matrix Fraction Description (LMFD). The performance of the extended algorithm is compared to the well-known MIMO four-step instrumental variable (IV4) algorithm. Monte Carlo simulations for different signal to noise ratios are conducted to assess the performance of the algorithm. Moreover, the algorithm is applied to a simulated quadruple tank process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.95-98
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• 2003

In this paper, an adaptive fuzzy neural control of unknown nonlinear systems based on the rapid learning algorithm is proposed for optimal parameterization. We combine the advantages of fuzzy control and neural network techniques to develop an adaptive fuzzy control system for updating nonlinear parameters of controller. The Fuzzy Neural Network(FNN), which is constructed by an equivalent four-layer connectionist network, is able to learn to control a process by updating the membership functions. The free parameters of the AFN controller are adjusted on-line according to the control law and adaptive law for the purpose of controlling the plant track a given trajectory and it's initial values are off-line preprocessing, In order to improve the convergence of the learning process, we propose a rapid learning algorithm which combines the error back-propagation algorithm with Aitken's $\delta$$\^$2/ algorithm. The heart of this approach ls to reduce the computational burden during the FNN learning process and to improve convergence speed. The simulation results for nonlinear plant demonstrate the control effectiveness of the proposed system for optimal parameterization.