• 한국정보통신학회논문지
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• 제10권1호
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• pp.88-95
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• 2006

PID 제어기는 구조가 간단하고 적용이 용이하다는 장점으로 인하여 널리 사용되고 있는 제어방식이다. 이러한 선형 PID 제어기는 시스템의 파라메터가 변화가 있거나 부하 특성이 비 선형적으로 변화할 때에 적절한 이득과 성능을 얻기 어려워 고성능 제어 특성을 기대하기 어렵다. 본 연구에서는 세포성 면역 반응과 경사감소학습에 기초하여 비선형 PID 제어기를 설계하고, 설계된 제어기의이득과 비선형 함수의 파라메터들을 실시간 적응적으로 학습할 수 있는 학습 알고리즘을 개발하고, 이를 제어시스템에 적용하였다. 제안된 비선형 PID 제어기는 비선형 직류 모터 시스템의 파라메터들이 변화하거나 주파수가 다른 추종 명령에 대하여, 적응적으로 이득을 변화 시키며 추종함을 보였다.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2002년도 하계학술대회 논문집 Vol.3 No.2
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• pp.1107-1112
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• 2002

An easy elevator originated is an opened system to compare an existing equipment, and learning efficient is high as a wiring that the sequence control circuit is on and off. The structure of an equipment to be controled from the first floor to the fifth floor is constructed by a lamp to express the function of the open-close of the door according to the cage moving, to express the mechanical actuation of the forward-reverse break and motor of load and of hand-worked control component of Push-Button S/W, L/S and Relay. In order to act of the elevator function that these components connected, designed the auto program and the sequence control circuit. Consequently the process that these(1~5steps) operated the cage with an auto program of the elevator and the sequence control circuit is controled by the step of forward and reverse that the L/S1~L/S5 of sensor adjust function let posit, by the adjustable S/W1~S/W5 of PLC testing panel and the S/W1~S/W5 which installed on the transparent acryl plate of a frame. In here, improved apparatus is the learning equipment of combined use to study the principle and the technique of the originated sequence control circuit and the auto program of PLC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 제37회 하계학술대회 논문집 D
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• pp.1868-1870
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• 2006

Neural network is used in many fields of control systems, but input-output patterns of a control system are not easy to be obtained and by using as single feedback neural network controller. And also it is difficult to get a satisfied performance when the changes of rapid load and disturbance are applied. To resolve those problems, this paper proposes a new algorithm which is the neural network controller. The new algorithm uses the neural network instead of activation function to control object at the output node. Therefore, control object is composed of neural network controller unifying activation function, and it supplies the error back propagation path to calculate the error at the output node. As a result, the input-output pattern problem of the controller which is resigned by the simple structure of neural network is solved, and real-time learning can be possible in general back propagation algorithm. Application of the new algorithm of neural network controller gives excellent performance for initial and tracking response and it shows the robust performance for rapid load change and disturbance. The proposed control algorithm is implemented on a high speed DSP, TMS320C32, for the speed of 3-phase induction motor. Enhanced performance is shown in the test of the speed control.

• 전자공학회논문지B
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• 제33B권1호
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• pp.178-186
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• 1996

오류를 최소화하는 방법에 기초한, 신경망에 대한 간단한 적응 집단 (population) 코딩 모델을 개발하였다. 이 모델은 원숭이의 자발적 팔운동에 있어서, 운동피질에서 발견되는 신경세포들의 집단 코딩의 성질과 잘 부합한다. 학습이 이루어진 후에, 특정의 방향성 모델 신경들을 제거함으로써, 이들 신경들의 코딩에 대한 기여를 조사하였다. 또, 나머지 신경들만을 가지고 학습을 시킴으로써, 그들 세포들의 선호 방향이, 코딩 오차를 줄이기 위해, 어떻게 변하는가를 관측하였다. 이와 같은 집단 코딩의 적응성은 아직 예측되거나 실험적으로 관측된 바가 없으므로, 집단코딩에 기초한 정보처리를 수행한다고 여겨지는 실제의 뇌피질에서도 유사한 적응성질이 존재하는지 조사해 보는 것도 흥미로울 것이다.

• Journal of Power Electronics
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• 제12권3호
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• pp.468-476
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• 2012

The interior permanent magnet synchronous motor (IPMSM) has been widely used in electric vehicle applications due to its excellent power to weigh ratio. This paper proposes the maximum torque control of an IPMSM drive using an adaptive learning (AL) fuzzy neural network (FNN) and an artificial neural network (ANN). This control method is applicable over the entire speed range while taking into consideration the limits of the inverter's rated current and voltage. This maximum torque control is an executed control through an optimal d-axis current that is calculated according to the operating conditions. This paper proposes a novel technique for the high performance speed control of an IPMSM using AL-FNN and ANN. The AL-FNN is a control algorithm that is a combination of adaptive control and a FNN. This control algorithm has a powerful numerical processing capability and a high adaptability. In addition, this paper proposes the speed control of an IPMSM using an AL-FNN, the estimation of speed using an ANN and a maximum torque control using the optimal d-axis current according to the operating conditions. The proposed control algorithm is applied to an IPMSM drive system. This paper demonstrates the validity of the proposed algorithms through result analysis based on experiments under various operating conditions.

• 한국전기전자재료학회논문지
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• 제16권4호
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• pp.351-357
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• 2003

An easy learning elevator originated is opened to compare the existed teaming equipment, and it had a high studied efficiency that the sequence control circuit can open and close with the wire. The structure of equipment to be controlled from the first floor to the fifth floors is demostrated by the constructive apparatus with the lamps to express the function of the open-close of the door according to the cage moving with a mechanical actuation of the forward reverse breaker and the motor of load, and the mechanical actuation of hand-operation control components of push-button S/W and L/S and relay etc. These components let connect each other in order to control of the elevator function with the auto program and the designed sequence control circuit. Consequently the cage could go and come till 1∼5 steps with an auto program of the elevator and the sequence control circuit. The sequence control circuit is controlled by the step of forward and reverse to follow as that the sensor function of L/S1 ∼ L/S5 let posit with the control switchs of S/W1 ∼ S/W5 of PLC testing panel and switchs of S/W1 ∼ S/W5 installed on the transparent acryl plate of the frame. In here, improved apparatus is the hand-auto operation combined learning equipment to study the principle and technique of the originate sequence control circuit and the auto program of PLC.

• Journal of Ginseng Research
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• 제18권3호
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• pp.165-174
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• 1994

To investigate the significant indicators Improving the undisturbed memory in animal behavior, we employed several behavioral methods (learning, relearning in radial maze, and active avoidance) with ginseng components. Results showed that the repeated intranasal administration of $Rb_1$ and total saponins from Korean red ginseng induced direct effects on the brain mechanisms in rats, and improved the spatial memory during the learning, relearning and retention in the 12-arm radial maze test. The intranasal treatment of the total saponins also effectively improved the disturbed memory (amnesia) by pentylentetrazole, and simultaneously protected the brain by decreasing the severity of motor epileptic seizures. The intraperitonial administration of polysaccharide fraction of Korean red ginseng could improve avoidance behavior (amount of the total ecapes) in the active-avoidance test. In addition, local changes of the temperature and resistance of skin observed after Rb, administration were suggested to reflect some action of sympathetic nerve Key words Memory, intranasal administration, pentylenetetrazole, Korea red ginseng.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.971-974
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• 2020

Infants express their physical and emotional needs to the outside world mainly through crying. However, most of parents find it challenging to understand the reason behind their babies' cries. Failure to correctly understand the cause of a baby' cry and take appropriate actions can affect the cognitive and motor development of newborns undergoing rapid brain development. In this paper, we propose an infant cry recognition system based on deep transfer learning to help parents identify crying babies' needs the same way a specialist would. The proposed system works by transforming the waveform of the cry signal into log-mel spectrogram, then uses the VGGish model pre-trained on AudioSet to extract a 128-dimensional feature vector from the spectrogram. Finally, a softmax function is used to classify the extracted feature vector and recognize the corresponding type of cry. The experimental results show that our method achieves a good performance exceeding 0.96 in precision and recall, and f1-score.

• 인간행동과 음악연구
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• 제3권1호
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• pp.63-76
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• 2006

1980년대 이후 음악과 학습에 관한 많은 연구들은 다양한 학습 기술에 필요한 인지기술의 영역에 대한 음악의 효과성을 계속해서 입증해 오고 있다. 음악과 학습에 관한 많은 연구들은 주로 음악의 인지기술과 학습의 세부적 기술들을 개별적으로 연관 지어 다루고 있으며, 음악이 비음악적 능력에 어떠한 영향을 미치는 지에 관심을 두고 있다. 이에 본 연구는 인지 학습기술과 음악적 인지기술과의 상관관계를 설명하고 있는 다양한 이론 및 연구들을 소개하고, 이를 통해 음악이 비음악적 능력 중 학습 기술에 어떠한 영향을 미치는 지를 정리해 보고자 하였다. 먼저 음악적 능력과 공간 지각력과의 상관관계를 설명하는 두 가지 이론으로서, "신경적 연계성(neural theories)" 이론과 "근접적 전이(near transfer)" 이론에 대해 살펴보았다. 이를 통해 음악적 기술과 공간적 기술을 담당하는 대뇌의 신경망 구조에서 음악 정보를 처리하는 과정이 어떻게 공간적-시간적 정보처리 과정과 연계되는 지를 설명하였다. 또한 음악이 학습과정에 필요한 주의력, 관찰력, 독립적 사고, 문제해결력, 비판적 사고 등을 강화시킨다고 제안하는 "동기이론"을 소개하였다. 이러한 이론들에 근거하여 음악과 학습기술과의 상관관계를 메타분석한 연구들을 살펴보았다. 많은 연구들이 음악기술과 학습기술의 상관관계는 물론 유의미한 인과 관계가 있음을 보여주었으며 이러한 결과들은 음악적 훈련 과정에서 습득되는 음악의 공간적, 시간적 개념이 학습기술에 긍정적인 영향을 미친다는 점을 지지한다. 다양한 학습기술에서도 공간 지각 능력을 주로 사용하는 수학과 읽기에 관한 연구가 많았는데, 특히 수학적 개념 중에서 분수나 집합 개념과 같은 추상적 개념들이 가장 높은 상관관계가 있었으며 읽기 능력에서는 시간적 개념에 근거한 단어 나열, 문자로 상징된 언어를 해석(decode)하는 기술이 강화된다는 점을 보여주었다. 음악과 학습과의 관계를 설명한 많은 연구들은 음악의 지각인지 기술이 다른 학습 분야에 전이된다는 사실을 이론적으로 지지하며, 또한 이러한 현상을 설명하는 세 가지 가설은 구조화된 음악활동이 학습 현장에 있는 아동들에게 효율적인 치료 교육적 개입이 될 수 있다는 근거를 제공할 수 있을 것이다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 춘계학술대회 논문집
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• pp.541-546
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• 2005

Tracking control of an automatic pipe cutting robot (APCROMB) is studied. Using magnetic force APCROMB, which is designed and developed in Kyung Hee University, binds itself to the pipe and executes unmanned cutting process. The gravity effect on the movement of APCROMB varies as it rotates around the cylindrical pipe laid in the gravitational field. To maintain a constant velocity and consistent cutting performance against the varying gravitational effect, the authors adopt a multi-rate repetitive learning controller (MRLC), which learns the required effort to cancel the repetitive tracking errors caused by nonlinear effect. In addition to the varying gravity effect other types of nonlinear disturbances including backlash in the driving system and the slip between the wheels of APCROMB and the pipe also cause degradation in the cutting process. In order to identify those nonlinear disturbances the position estimation based on the encoder attached at the motor is not good enough. To identify the absolute angular position of APCROMB the authors propose the angular position estimation based on the signals from a MEMS-type two-axis accelerometer mounted on APCROMB. The tracking performances of APCROMB with a MRLC using the encoder-based position estimation is experimentally measured and results are shown. Also the difference between the encoder-based angular displacement measurement and the accelerometerbased angular displacement measurement is included.