• 한국생산제조학회지
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• 제6권1호
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• 한국정밀공학회지
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• 제22권9호
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• pp.137-146
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• 2005

This paper describes a research work to develop a computer-aided design for the product made by progressive working of bending and piercing. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in AutoLISP on the AutoCAD with a personal computer and is composed of three main modules, which are input and shape treatment, flat pattern layout, strip layout modules. The system is designed by considering several factors, such as piercing and bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic forms, including piercing and bending sequences with punch profiles divided into for external area. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• 소음진동
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• 제11권1호
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• pp.125-131
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• 2001

There is a clearance between the parts of a machine due to design tolerance, manufacturing error, wear, looseness, or misalignment. If the clearance is large, the vibration and noise of the machine is generally large. Therefore, the analysis on the nitration and noise of a machine can tell the clearance of the machine, which reveals the condition of the machine, i.e., the existence of faults and the safety of the machine. The investigation of this kind of research should be on the basis of experimental results. A link mechanism with a clearance at a joint between the coupler and locker is made for the investigation of the condition monitoring of a machine due to clearance. The vibration and sound are measured from the link driving system during the operation. The signals are clarified using line enhancement technique. The noise removed signals are used to develop the dynamic model of the system for a model based fault diagnosis. Also this study showed that the clarified signals can be used for the calculation of the joint forces between the coupler and rocker and for the correlation between the vibration and sound levels and the clearance sizes.

• 한국정보처리학회논문지
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• 제7권12호
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• pp.3804-3814
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• 2000

본 논문에서는 실시간 객체 모델인 TMO(Time-triggered Message-triggered Object)에 기반을 둔 실시간 객체지향 프로그램의 시간 제약이 제대로 만족되는가를 시스템 수행 중에 감시하기 위한 모니터의 효과적인 구현 방안에 대하여 논한다. 구현 환경으로 윈도우 OS상의 TMO 프로그램 실행 환경인 WTMOS(Windows TMO System)를 이용하였고, 감시 주체가 되는 수행 시간 모니터의 성능 분석을 위하여 온도 제어를 위한 응용 시스템이 구축되었다. 모니터 대상과 모니터 조건을 TMO 프로그램내에 명시하는 방법과 정의된 모니터의 기능을 WTMOS 내부와 TMO 형태의 응용 객체로 분산시켜서 적은 비용으로 시스템을 구축하는 방법을 제시한다.

• 한국멀티미디어학회논문지
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• 제6권7호
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• pp.1189-1199
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• 2003

본 논문에서는 계층화 모션 추정법과 병렬 처리를 이용한 차량의 움직임 측정 알고리즘을 제안한다. 본 시스템에서는 CMOS 센서를 통하여 도로 영상을 캡쳐한다. 그 다음에 영상을 작은 블록들로 나누고 블록매칭을 이용하여 각 블록의 움직임을 계산한다. 그리고 움직임이 비슷한 블록들을 클러스터링하여 차량의 움직임을 측정한다. 본 논문에서는 실시간 동작을 위하여 계층화 모션 추정법과 병렬 처리에 의거한 블록매칭 알고리즘을 제안한다. 병렬처리를 위해서는 파이프라인과 데이터 플로우 기법을 도입하였다. 본 논문에서 제안된 시스템은 기존의 내장형 시스템을 이용하여 구현되었다. 제안된 블록매칭 알고리즘은 PLD(Programmable Logic Device)를 이용하여 구현하였고 클러스터링 알고리즘은 ARM 프로세서를 이용하여 구현하였다. 실험 결과에 의하면 본 논문에서 구현된 시스템은 차량의 움직임을 실시간으로 추출할 수 있었다.

• Journal of Power Electronics
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• 제16권4호
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• pp.1438-1454
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• 2016

Because the nonlinear and time-varying characteristics of continuously variable transmission (CVT) systems driven by means of a six-phase copper rotor induction motor (CRIM) are unconscious, the control performance obtained for classical linear controllers is disappointing, when compared to more complex, nonlinear control methods. A blend modified recurrent Gegenbauer orthogonal polynomial neural network (OPNN) control system which has the online learning capability to come back to a nonlinear time-varying system, was complied to overcome difficulty in the design of a linear controller for six-phase CRIM driving CVT systems with lumped nonlinear load disturbances. The blend modified recurrent Gegenbauer OPNN control system can carry out examiner control, modified recurrent Gegenbauer OPNN control, and reimbursed control. Additionally, the adaptation law of the online parameters in the modified recurrent Gegenbauer OPNN is established on the Lyapunov stability theorem. The use of an amended artificial bee colony (ABC) optimization technique brought about two optimal learning rates for the parameters, which helped reform convergence. Finally, a comparison of the experimental results of the present study with those of previous studies demonstrates the high control performance of the proposed control scheme.

• 전력전자학회논문지
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• 제16권2호
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• pp.105-113
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• 2011

태양광 발전 시스템이 대용량화됨에 따라 태양전지 어레이 구성 시 부정합(mismatch) 문제가 대두되는 가운데, 태양전지 모듈을 직접 계통에 연계하는 AC 모듈형 태양광 모듈 집적형 전력변환장치(PV-MIC)에 관한 연구가 지속되고 있다. PV-MIC는 수명 및 고효율이 가장 큰 문제이며 이 문제를 해결하기 위해서 본 논문에서는 ZVS 동작을 통하여 스위칭 손실을 저감시키고 입력전류 리플감소를 통하여 입력 커패시턴스를 저감할 수 있는 능동 클램프 전류원 하프 브릿지 컨버터를 적용한 PV-MIC를 제안하고, 이에 관한 제어분담 및 설계에 대하여 고찰한다.

• 한국정보과학회논문지:시스템및이론
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• 제29권6호
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• pp.354-360
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• 2002

지연시간 계산은 지연시간을 고려한 배치 단계에서 백만 번 이상도 수행되므로 효과적이면서 간단해야 한다. 본 논문에서는 계산은 매우 빠르고 간단하지만 수 백%의 오차를 가질 수 있는 Elmore delay를 개선하기 위해 Elmore delay와 SPICE 결과의 비율을 보상값으로 이용하는 방법을 제안한다. 제안한 새로운 방법은 resistance shielding effects를 고려하여 실험적으로 지연시간을 보상하여 그 오차를 크게 줄이며, 계산 복잡도는 Elmore delay와 같은 정도로 간단하다. Elmore delay가 31.6 ~ 145.2% 오차를 갖는 RC 트리에 대하여 실험한 결과, 보상된 delay의 오차는 2.5 ~ 22.7%로 크게 줄었다.

• Journal of Electrical Engineering and Technology
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• 제13권6호
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.1109-1114
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• 2007

This paper presents the road simulator control technology for reproducing the road input signal to implement the real road data. The simulator consists of the hydraulic pump, servo valve, hydraulic actuator and its control equipment. The QFT is utilized to control the simulator effectively. The control system illustrates a tracking performance of the closed-loop controller with low order transfer function G(s) and pre-filter F(s) for a parametric uncertain model. A force controller is designed to communicate the control signal between simulator and digital controller. The efficacy of the QFT force controller is verified through the numerical simulation, in which combined dynamics and actuation of the hydraulic servo system are tested. The simulation results show that the proposed control technique works well under uncertain hydraulic plant system. The conventional software (Labview) is used to make up for the real controller in the real-time basis, and the experimental works show that the proposed algorithm works well for a single road simulator.