• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.115-118
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• 2000

We present a new variable step size LMS algorithm using the correlation between reference input and error signal of adaptive filter. The proposed algorithm updates each weight of filter by different step size at same sample time. We applied this algorithm to adaptive multip]e-notch filter. Simulation results are presented to compare the performance of the proposed algorithm with the usual LMS algorithm and another variable step algorithm.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.1
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• pp.1-8
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• 2019

In this study, a maximum power point tracking (MPPT) algorithm based on the perturb and observe (P&O) method with variable step size is proposed to improve the dynamic response characteristic of MPPT, using the existing P&O method. The proposed algorithm, which we verified by simulation and experiment, can track the maximum power point (MPP) through duty control and consisted of three operation modes, namely, constant voltage mode, fast mode, and variable step mode. When the insolation is constant, the voltage variation of the operating point at the MPP is reduced through the step size reduction of the duty in the variable step mode. Consequently, the vibration of the operating point is reduced, and the power generation efficiency is increased. When the insolation changes, the duty and the photovoltaic (PV) voltage are kept constant through the constant voltage mode. The operating point then rapidly tracks the new MPP through the fast-mode operation at the end of the insolation change. When the MPP is reached, the operation is changed to the variable step mode to reduce the duty step size and track the MPP. The validity of the proposed algorithm is verified by simulation and experiment of a PV system composed of a PV panel and a boost converter.

• Journal of Drive and Control
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• v.15 no.2
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• pp.9-21
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• 2018

The aim of this study was to develop and test a model of an auto-sensing hydraulic breaker that can automatically change its 4-step impact mode according to the rock strength using SimulationX. The auto-sensing hydraulic breaker with a 4-step variable impact mode has the advantage of obtaining optimal impact energy and impact frequency under various rock conditions compared to an auto-sensing hydraulic breaker with a 2-step variable impact mode, which has already been developed overseas. Several steps were necessary to conduct this study. First, the operation principle of the auto-sensing hydraulic breaker with the 2-step variable impact mode was analyzed. Based on the findings, an analysis model of the auto-sensing hydraulic breaker with the 4-step variable impact mode was developed (and compared with the 2-step variable impact mode) Finally, an analysis of the results established that the stepwise variable of the impact mode was implemented according to the rock strength and the difference of each impact mode was confirmed. This study is expected to contribute to the development of auto-sensing hydraulic breakers that are superior to those developed by advanced companies in foreign countries.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.566-569
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• 1987

The primary difficulties encountered in the use of step motors are underdamped response when stopping at a specified position and dynamic instability during high-speed slewing. This paper proposes a speed and position detection scheme using the back EMF generated by the rotating permanent magnet field of a two-phase 1.8.deg. hybrid step motor, and presents its application to the state-variable feedback control of the hybrid step motor. All simulation results in a single step response show that the hybrid step motor performances such as peak overshoot and settling time are greatly improved.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.165-171
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• 2006

This paper proposes a data fusion algorithm of nonlinear multi sensor dynamic systems of synchronous sampling based on filtering step by step. Firstly, the object state variable at the next time index can be predicted by the previous global information with the systems, then the predicted estimation can be updated in turn by use of the extended Kalman filter when all of the observations aiming at the target state variable arrive. Finally a fusion estimation of the object state variable is obtained based on the system global information. Synchronously, we formulate the new algorithm and compare its performances with those of the traditional nonlinear centralized and distributed data fusion algorithms by the indexes that include the computational complexity, data communicational burden, time delay and estimation accuracy, etc.. These compared results indicate that the performance from the new algorithm is superior to the performances from the two traditional nonlinear data fusion algorithms.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.47-55
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• 2019

It is important to identify informative variables in high dimensional data analysis; however, it becomes a challenging task when covariates are contaminated by measurement error due to the bias induced by measurement error. In this article, we present a two-step approach for variable selection in the presence of measurement error. In the first step, we directly select important variables from the contaminated covariates as if there is no measurement error. We then apply, in the following step, orthogonal regression to obtain the unbiased estimates of regression coefficients identified in the previous step. In addition, we propose a modification of the two-step approach to further enhance the variable selection performance. Various simulation studies demonstrate the promising performance of the proposed method.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1104-1111
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• 2003

The paper presents an algorithm for the compensation of gain and phase imbalances to exist between I-phase and Q-phase signal at direct conversion receiver. We propose a gain and phase imbalances blind equalization compensation algorithm by using variable step-size adaptive loop at direct conversion receiver. The blind equalization schemes have trade-off between convergence speed and jitter effect for the compensation of gain and phase imbalance. We propose the variable step-size adaptive loop method, which varies the loop coefficients according to errors, for recovering these problem. By using variable step-size adaptive loops, we propose to speed up the convergence process and reduce the jitter effect and simulation results show that the algorithm compensates signal loss and speeds up convergence time.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.815-821
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• 2009

Information processing in variable and noisy environments is usually accomplished by means of adaptive filters. Among various adaptive algorithms, Least Mean Square (LMS) has become the most popular for its robustness, good tracking capabilities and simplicity, both in terms of computational load and easiness of implementation. In practical application of the LMS algorithm, the most important key parameter is the Step Size. As is well known, if the Step Size is large, the convergence rate of the algorithm will be rapid, but the steady state mean square error (MSE) will increase. On the other hand, if the Step Size is small, the steady state MSE will be small, but the convergence rate will be slow. Many researches have been proposed to alleviate this drawback by using a variable Step Size. In this paper, a new variable Step Size LMS(VSSLMS) called Categorized VSSLMS (CVSSLMS) is proposed. CVSSLMS updates the Step Size by categorizing the current status of the gradient, hence significantly improves the convergence rate. The performance of the proposed algorithm was verified from the view point of convergence rate, Excessive Mean Square Error(EMSE), and complexity through experiments.

• Journal of Power Electronics
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• v.12 no.1
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• pp.164-171
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• 2012

Variable step size maximum power point trackers (MPPTs) are widely used in photovoltaic (PV) systems to extract the peak array power which depends on solar irradiation and array temperature. One essential factor which judges system dynamics and steady state performances is the scaling factor (N), which is used to update the controlling equation in the tracking algorithm to determine a new duty cycle. This paper proposes a novel stability study of variable step size incremental resistance maximum power point tracking (INR MPPT). The main contribution of this analysis appears when developing the overall small signal model of the PV system. Therefore, by using linear control theory, the boundary value of the scaling factor can be determined. The theoretical analysis and the design principle of the proposed stability analysis have been validated using MATLAB simulations, and experimentally using a fixed point digital signal processor (TMS320F2808).