• Journal of IKEEE
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• v.23 no.3
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• pp.893-898
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• 2019

Time-frequency representations are methods to display the magnitude or energy density of a signal on the two dimensional plane of both time and frequency. They are useful in analyzing the characteristics of time-varying signals. Music is a typical time-varying signal, and it can be analyzed by time-frequency representations. Recently, it is popular to change the sound quality by attaching a safety sounder to an instrument. It is performed to improve perception subjectively by spending little cost and modifying sound quality. In time domain, it is difficult to notify the difference between music signals with and without the sounder. But, it is easy to find the difference in frequency domain or in time-frequency domain. In this paper, the music signal from a flute with sounder is analyzed both in the frequency domain and in the time-frequency domain. It is confirmed that the frequency components in the mid-frequency range of 500~2500 are reinforced.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10a
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• pp.842-846
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• 1987

This paper proves that a filter for scramble spectrum is realized by a periodically time-varying digital filter. Further, we propose a design method of this filter by using a bi-frequency map. As an example, we implemented this filter with Digital Signal Processor.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.61.2-61
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• 2002

$\textbullet$ Introduction $\textbullet$ Dynamics of robotic manipulator $\textbullet$ Time-varying sliding surface $\textbullet$ Fuzzy rule, Membership function $\textbullet$ Application to a two degree robotic manipulator $\textbullet$ Conclusion

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.494-498
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• 1989

This paper describes an efficient time-varying parameter estimation algorithm by resetting the parameter and P matrix of the RLS algorithm. The described algorithm is useful for estimating both jump parameter and drifting parameter which vary quite rapidly.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.245-248
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• 2002

본 논문에서는 이동체에 Beam Loss를 위한 분석적 모델을 소개하고 시변 방위 추정 알고리즘을 적용하였을 때와 일반 알고리즘을 적용했을 때의 성능개선 정도를 비교한다.

• Smart Structures and Systems
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• v.9 no.4
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• pp.373-392
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• 2012

Tracking control of systems with variable stiffness hysteresis using a gain-scheduled (GS) controller is developed in this paper. Variable stiffness hysteretic system is represented as quasi linear parameter dependent system with known bounds on parameters. Assuming that the parameters can be measured or estimated in real-time, a GS controller that ensures the performance and the stability of the closed-loop system over the entire range of parameter variation is designed. The proposed method is implemented on a spring-mass system which consists of a semi-active independently variable stiffness (SAIVS) device that exhibits hysteresis and precisely controllable stiffness change in real-time. The SAIVS system with variable stiffness hysteresis is represented as quasi linear parameter varying (LPV) system with two parameters: linear time-varying stiffness (parameter with slow variation rate) and stiffness of the friction-hysteresis (parameter with high variation rate). The proposed LPV-GS controller can accommodate both slow and fast varying parameter, which was not possible with the controllers proposed in the prior studies. Effectiveness of the proposed controller is demonstrated by comparing the results with a fixed robust $\mathcal{H}_{\infty}$ controller that assumes the parameter variation as an uncertainty. Superior performance of the LPV-GS over the robust $\mathcal{H}_{\infty}$ controller is demonstrated for varying stiffness hysteresis of SAIVS device and for different ranges of tracking displacements. The LPV-GS controller is capable of adapting to any parameter changes whereas the $\mathcal{H}_{\infty}$ controller is effective only when the system parameters are in the vicinity of the nominal plant parameters for which the controller is designed. The robust $\mathcal{H}_{\infty}$ controller becomes unstable under large parameter variations but the LPV-GS will ensure stability and guarantee the desired closed-loop performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1422-1431
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• 2015

The reliability of power system components can be affected by a numbers of factors such as the health level of components, external environment and operation environment of power systems. These factors also affect the electrical parameters of power system components for example the thermal capacity of a transmission element. The relationship of component reliability and power system is, therefore, a complex nonlinear function related to the above-mentioned factors. Traditional approaches for reliability assessment of power systems do not take the influence of these factors into account. The assessment results could not, therefore, reflect the short-term trend of the system reliability performance considering the influence of the key factors and provide the system dispatchers with enough information to make decent operational decisions. This paper discusses some of these important operational issues from the perspective of power system reliability. The discussions include operational reliability of power systems, reliability influence models for main performance parameters of components, time-varying reliability models of components, and a reliability assessment algorithm for power system operations considering the time-varying characteristic of various parameters. The significance of these discussions and applications of the proposed techniques are illustrated by case study results using the IEEE-RTS.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.14-20
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• 2009

In this paper, the time-varying failure rate to consider climate effect was extracted. Even if the same kind of equipments is estimated for extracting the time-varying failure rate, the failure rates could be different depending on external effect such as climate. With the consequence, the failure rate extracted to consider the climate effect is necessary for using the failure rate on the optimal investment plan or asset management, To consider the characteristic of climate effects(Classified into 5 categories, heavy rain, thunderbolt, strong wind, tidal waves, no character), the survey of officers charging the operation of equipment in KEPCO branch office was done. With this consequence, this paper suggest the failure rate extraction method to consider the climate effect analyzed by the survey.

• Smart Structures and Systems
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• v.22 no.3
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• pp.359-368
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• 2018

A method is proposed for the identification of instantaneous frequencies (IFs) in time-varying structures. The proposed method combines a maximum gradient algorithm and a smoothing operation. The maximum gradient algorithm is designed to extract the wavelet ridges of response signals. The smoothing operation, based on a polynomial curve fitting algorithm and a threshold method, is employed to reduce the effects of random noises. To verify the effectiveness and accuracy of the proposed method, a numerical example of a signal with two frequency modulated components is investigated and an experimental test on a steel cable with time-varying tensions is also conducted. The results demonstrate that the proposed method can extract IFs from the noisy multi-component signals and practical response signals successfully. In addition, the proposed method can provide a better IF identification results than the standard synchrosqueezing wavelet transform.