• Proceedings of the KIEE Conference
• /
• 2001.07b
• /
• pp.1005-1008
• /
• 2001

This paper presents average current-mode control AC/DC ZVT(Zero Voltage Transition) Boost Converter. This boost converter perceives feed forward signal of input and feedback signal of output for average current-mode control proposed converter employs active-clamp method for ZVT. This converter gives the good PFC(Power Factor Correction), low line current hormonic distortions and tight output voltage regulations. This converter also has a high efficiency by active-clamp method. The principle of operation, feature, and design considerations are illustrated and verified through the experiment with a 150W, 120kHz prototype converter.

• Proceedings of the KIEE Conference
• /
• 2006.07d
• /
• pp.2089-2090
• /
• 2006

본 논문은 기호 코딩 및 정보입자를 이용한 유전자 알고리즘의 전방향 퍼지 집합 기반 뉴럴네트워크 (Information Granules and Symbolic Encoding-based Fuzzy Set Polynomial Neural Networks ; IG and SE based FSPNN)의 모델 설계를 제안한다. 기존 퍼지 집합기반 다항식 뉴럴네트워크(FSPNN)의 구조 최적화를 위해 이진코딩을 사용하였다. 그러나 이진코딩에서 스트링의 길이가 길면 길수록 인접한 두 수 사이에 발생하는 급격한 비트 차이라는 해밍절벽이 발생하였다. 이에 제안된 모델에서는 해밍절벽의 문제를 해결하기 위해 기호코딩을 사용하였다. 제안된 모델은 각 입력에 대해 MFs의 개수 만큼 규칙을 생성하는 Fuzzy 집합기반 다항식 뉴럴네트워크(FSPNN)를 그대로 사용한다. 그리고 IG based gFSPNN의 평가을 위해 실험적 예제를 통하여 제안된 모델의 성능 및 근사화 능력의 우수함을 보인다.

• Structural Engineering and Mechanics
• /
• v.52 no.1
• /
• pp.97-113
• /
• 2014

In the present work appropriate concrete material models have been proposed to predict drying shrinkage and specific creep of High-performance concrete (HPC) using Artificial Neural Network (ANN). The ANN models are trained, tested and validated using 106 different experimental measured set of data collected from different literatures. The developed models consist of 12 input parameters which include quantities of ingredients namely ordinary Portland cement, fly ash, silica fume, ground granulated blast-furnace slag, water, and other aggregate to cement ratio, volume to surface area ratio, compressive strength at age of loading, relative humidity, age of drying commencement and age of concrete. The Feed-forward backpropagation networks with Levenberg-Marquardt training function are chosen for proposed ANN models and same implemented on MATLAB platform. The results shows that the proposed ANN models are more rational as well as computationally more efficient to predict time-dependent properties of drying shrinkage and specific creep of HPC with high level accuracy.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.737-741
• /
• 1994

We show an application of a genetic algorithm to, control systems including neural networks. Genetic algorithms are getting more popular nowadays because of their simplicity and robustness. Genetic algorithms are global search techniques for optimization and many other problems. A feed-forward neural network which is widely used in control applications usually learns by error back propagation algorithm(EBP). But, when there exist certain constraints, EBP can not be applied. We apply a modified genetic algorithm to such a case. We show simulation examples of two cart-pole nonlinear systems: single pole and double pole.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.306-309
• /
• 1996

This paper presents a method of landmark recognition in indoor environments using a neural-network for an autonomous mobile robot. In order to adapt to image deformation of a landmark resulted from variations of view-points and distances, a multi-labeled template matching(MLTM) method and a dynamic area search method(DASM) are proposed. The MLTM is. used for matching an image template with deformed real images and the DASM is proposed to detect correct feature points among incorrect feature points. Finally a feed-forward neural-network using back-propagation algorithm is adopted for recognizing the landmark.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.660-663
• /
• 1996

There has been many activity to increase accuracy in machining center by reducing tracking error. The tracking error can cause bad effect in high speed rigid tapping in which syncronization servo motor with spindle is relatively important. To reduce tracking error, feed forward control has been used, but no method is provided knowing motor dynamics, force variation, etc. In this paper, we observe that, despite of tracking error of relevant axis, high speed tapping could be possible by reducing contour error of axis to be syncronized. We present the method to increase accuracy in high speed tapping to minimize contour error by automatically fitting gains of servo and spindle.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.281-286
• /
• 2005

The main objective of the research work presented in this article is to present a systematic approach for designing a multilayer feed-forward artificial neural network based self-tuning power system stabilizer (ST-ANNPSS). In order to suggest an approach for selecting the number of neurons in the hidden layer, the dynamic performance of the system with ST-ANNPSS is studied and hence compared with that of conventional PSS. Finally the effect of variation of loading condition and equivalent reactance, Xe is investigated on dynamic performance of the system with ST-ANNPSS. Investigations reveal that ANN with one hidden layer comprising nine neurons is adequate and sufficient for ST-ANNPSS. Studies show that the dynamic performance of STANNPSS is quite superior to that of conventional PSS for the loading condition different from the nominal. Also it is revealed that the performance of ST-ANNPSS is quite robust to a wide variation in loading condition.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1741-1744
• /
• 2005

In this paper, we proposed an adaptive skill element based on error signal. We assume that human progress their skills of actions based on errors, then an inverse dynamic of human motion have to changes. Human controller consists from feedback element (FB) and feed forward element (FF) and their elements cooperate to control actions. Under the assumption, we vary the connection of FF and FB by error signal. We propose the index function for change of a skill parameter. From results of the numerical simulations for the varying skill parameter with index function, we consider that the position error given by our vision changes the skill element and we confirm that the position error is the one of the estimate function for the improvement in our skill.

• Journal of Industrial Technology
• /
• v.24 no.A
• /
• pp.99-107
• /
• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and the environments as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to parition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum of the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.11a
• /
• pp.243-246
• /
• 2000

Productivty of tapping has been increasing through the tcchnological advances in synchronization between spindle rotation and feed motion even in the high spindle speed. However, not much researches have been conducted about tapping process because its complicate cutting mechanism. In order ta investigate the characteristics of the tapping process, this paper concentrates on the analysis of curting torque behavior during one cycle of lapping. As one completc thread is performed through the whole chamfer ercuttlng, cutting torque increases highly in chamfer cutting, but smaothly in full thread cutting Functioning of the threads guide. Cutting torque in backward cutting is smaller than in Sorwerd cutting due to only friction farce in against between the tool and workpiece. And torque behavior of a periodic Sine ripple-mark was identified during one revolution of a tap.