• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.425-436
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• 2016

In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.170-173
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• 2005

This paper presents an Fuzzy-Neuro Observer system for an ac servo motor dirve to track periodic commands using a neuro-fuzzy observer. AC servo motor drive system is rather similar to a linear system. However, the uncertainties, such as machanical parametric variation, external disturbance, uncertainty due to nonideal in transient state. therefore an intelligent control system that isan on-line trained neural network controller with adaptive learning rates.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.172-177
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• 2001

This paper proposes an adaptive feedforward controller (AFC) based on LMS for periodic disturbance rejection in active magnetic bearing system. The proposed controller does not alter the stability and robustness of the existing AMB system. It is shown that the control delay due to the eddy current as well as runout and unbalance can be identified and compensated using the estimated displacement from the measured magnetic flux. The simulation results confirm that the proposed scheme successfully identifies and compensates for the runout, unbalance and eddy current effect, leading to a high-precision magnetic bearing system.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1771-1772
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• 2008

전동기나 발전기와 같은 회전기기에 주로 발생하는 주기외란은 시스템 성능을 저하시키는 특성으로서 고급제어시스템 구현을 위하여 반드시 보상되어야 한다. 본 논문은 신호처리기법의 일종인 Lock In Amplifier(LIA) 알고리즘 기반 외란보상 제어기를 제안한다. 제안하는 제어규칙은 공칭제어기와 보조제어기로 구성되며 전자는 외란을 고려하지 않은 시스템 모델에 대하여 상태궤환 제어기법으로 산출되며 후자는 LIA 기법을 이용하여 외란특성을 실시간으로 추정하여 연산되어진다. 제안하는 제어시스템은 기존의 결정적 외란으로부터 발생되었던 실시간 제어오차를 월등히 개선하는 장점을 가지고 있다. 실시간 전동기 제어장치를 통해 제안하는 알고리즘의 성능의 우수성 및 타당성을 검증한다.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.566-572
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• 2000

The System identification is the process of developing or improving a mathematical model of a physical system using experimental data of the input, output and noise relationship. The field of system identification has been an important discipline within the automatic control area. The reason is the requirement that mathematical models having a specified accuracy must be used to apply modem control methods. In this paper, it is confirmed that we can obtain transfer function of flexible beam that is expressed in the forms of identified state-space system matrix A, B, C, D and identified observer gain G using Eigensystem Realization Algorithm including singular value decomposition. And these matrices can be applied to the automatic control. In addition to, it is also confirmed that transfer function can express a system using identified observer gain G, in spite of a noisy data or a periodic disturbance.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.362-362
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• 2000

The purpose of this thesis is to reduce force ripple of linear pulse motor(LPM) using neural network and to enhance precision. In order to this, we propose a new controller using a neural network to compensate disturbances. The structure includes adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances. The proposed controller compensates an unmodeled dynamics in the LPM. The neural network changes a current command to reduce position error and force ripple of the LPM. We compare proposed controller with PI controller. Simulation result shows that the proposed controller has better performance than a PI controller without neural network.

• Sleep Medicine and Psychophysiology
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• v.14 no.1
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• pp.5-12
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• 2007

Sleep changes substantially with age. There is a phase advance in the circadian sleep cycle and increased waking after sleep onset. The elderly people wake more frequently during the night and experience fragmented sleep and excessive daytime sleepiness. The prevalence of sleep disorders increases with age, and the composition of sleep disorders in the elderly differs from that in the young. The most frequently encountered sleep disorders are psychophysiologic insomnia, sleep disturbance due to dementia, sleeprelated respiratory disorder, restless legs syndrome and periodic limb movement disorder, and REM sleep behavior disorder. To treat the elderly sleep problem appropriately, it is important to know how sleep pattern changes as we age and to understand the cause of sleep-related symptoms. This article will review the sleep physiology and common sleep disorders in the elderly.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.1415-1419
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• 1990

A novel type of a play-back servo system with high precision is designed using an iterative learning control method by employing the model algorithmic control concept together with an inverse model. A sufficient condition is also provided for the convergency. It is shown by simulation that the proposed control algorithm yields a good performance even in the presence of a periodic load disturbance and proved by experiments using microprocessor-based play-back servo system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.215-222
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• 2017

An active synthetic aperture sonar mounted on small UUV is generated various trajectory disturbances in the traveling path by the influence of external underwater environments. That is the phase mismatch occurs in the synthetic aperture processing of the signals reflected from seabed objects and fetches the detection performance decreases. In this paper, we compensated deteriorated images by the active SAS autofocus processing using DPC and analyzed the effects of detection performance when the periodic trajectory disturbances occur in the side direction at a constant velocity and straight movement of UUV. Through simulations, the deteriorated images according to the periodic disturbance magnitudes and period variations in the platform were compensated using difference phases processing of the overlapping displaced phase centers on the adjacent transmitted ping signals, and we conformed the improved performance characteristics of azimuth resolution and detection images at 3dB reference point.

• Sleep Medicine and Psychophysiology
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• v.17 no.2
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• pp.75-84
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• 2010

The cyclic alternating pattern (CAP) is a periodic EEG activity in NREM sleep, characterized by sequences of transient electrocortical events that are distinct from background EEG activities. A CAP cycle consists of two periodic EEG features, phase A and subsequent phase B whose durations are 2-60 s. At least two consecutive CAP cycles are required to define a CAP sequence. The CAP phase A is a phasic EEG event, such as delta bursts, vertex sharp transients, K-complex sequences, polyphasic bursts, K-alpha, intermittent alpha, and arousals. Phase B is repetitive periods of background EEG activity. The absence of CAP more than 60 seconds or an isolated phase A is classified as non-CAP. Phase A activities can be classified into three subtypes (A1, A2, and A3), based on the amounts of high-voltage slow waves (EEG synchrony) and low-amplitude fast rhythms (EEG desynchrony). CAP rate, the percentage of CAP durations in NREM sleep is considered to be a physiologic marker of the NREM sleep instability. In insomnia, the frequent discrepancy between self-reports and polysomnographic findings could be attributed to subtle abnormalities in the sleep tracing, which are overlooked by the conventional scoring methods. The conventional scoring scheme has superiority in analysis of macrostructure of sleep but shows limited power in finding arousals and transient EEG events that are major component of microstructure of sleep. But, it has recently been found that a significant correlation exists between CAP rate and the subjective estimates of the sleep quality in insomniacs and sleep-improving treatments often reduce the amount of CAP. Thus, the extension of conventional sleep measures with the new CAP variables, which appear to be the more sensitive to sleep disturbance, may improve our knowledge on the diagnosis and management of insomnia.