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적응 퍼지제어기를 이용한 분산 Multi Vehicle의 컬러인식을 통한 물체이송에 관한 연구
김훈모,Kim, Hun-Mo 대한기계학회 2001 大韓機械學會論文集A Vol.25 No.2
In this paper, we present a collaborative method for material delivery using a distributed vehicle agents system. Generally used AGV(Autonomous Guided Vehicle) systems in FA require extraordinary facilities like guidepaths and landmarks and have numerous limitations for application in different environments. Moreover in the case of controlling multi vehicles, the necessity for developing corporation abilities like loading and unloading materials between vehicles including different types is increasing nowadays for automation of material flow. Thus to compensate and improve the functions of AGV, it is important to endow vehicles with the intelligence to recognize environments and goods and to determine the goal point to approach. In this study we propose an interaction method between hetero-type vehicles and adaptive fuzzy logic controllers for sensor-based path planning methods and material identifying methods which recognizes color. For the purpose of carrying materials to the goal, simple color sensor is used instead vision system to search for material and recognize its color in order to determine the goal point to transfer it to. The proposed method reaveals a great deal of improvement on its performance.
적응 학습방식의 신경망을 이용한 좌심실보조장치의 모델링
김상현,김훈모,류정우,Kim, Sang-Hyun,Kim, Hun-Mo,Ryu, Jung-Woo 대한의용생체공학회 1996 의공학회지 Vol.17 No.3
This paper presents a Neural Network Identification(NNI) method for modeling of highly complicated nonlinear and time varing human system with a pneumatically driven mock circulatory system of Left Ventricular Assist Device(LVAD). This system consists of electronic circuits and pneumatic driving circuits. The initiation of systole and the pumping duration can be determined by the computer program. The line pressure from a pressure transducer inserted in the pneumatic line was recorded System modeling is completed using the adaptively trained backpropagation learning algorithms with input variables, heart rate(HR), systole-diastole rate(SDR), which can vary state of system. Output parameters are preload, afterload which indicate the systemic dynamic characteristics. Consequently, the neural network shows good approximation of nonlinearity, and characteristics of left Ventricular Assist Device. Our results show that the neural network leads to a significant improvement in the modeling of highly nonlinear Left Ventricular Assist Device.
김상현,정성택,김훈모,Kim, Sang-Hyeon,Jeong, Seong-Taek,Kim, Hun-Mo 대한의용생체공학회 1998 의공학회지 Vol.19 No.1
본 연구에서 복잡한 비선형적 특성을 갖는 공압식 좌심실보조장치의 모델링과 제어에 인공신경망을 제안하였다. 일반적으로 좌심실보조장치는 비선형이 보상되어야 하는데 인공신경망은 학습능력에 의해 비선형 동적 시스템의 제어에 적용될 수 있다. 인공신경망 모델링을 통해 좌심실 보조장치의 동적 모델을 모델링하고 이를 기반으로 하여 인공신경망 제어기가 설계되었다. 제안된 알고리즘을 이용한 좌심실보조장치의 모델링과 제어성능 및 유효성은 컴퓨터 시뮬레이션에 의해 증명되었다. In this paper, we present a neural network identification and a control of highly complicated nonlinear left ventricular assist device(LVAD) system with a pneumatically driven mock circulation system. Generally, the LVAD system needs to compensate for nonlinearities. It is necessary to apply high performance control techniques. Fortunately, the neural network can be applied to control of a nonlinear dynamic system by learning capability. In this study, we identify the LVAD system with neural network identification(NNI). Once the NNI has learned the dynamic model of the LVAD system, the other network, called neural network controller(NNC), is designed for a control of the LVAD system. The ability and effectiveness of identifying and controlling the LVAD system using the proposed algorithm will be demonstrated by computer simulation.
석창성,김정표,송성진,김훈모,김재원,김수용,Seok, Chang-Seong,Kim, Jeong-Pyo,Song, Seong-Jin,Kim, Hun-Mo,Kim, Jae-Won,Kim, Su-Yong 대한기계학회 2001 大韓機械學會論文集A Vol.25 No.12
The BI(Ball Indentation) method has a potential to assess the mechanical properties and to replace conventional fracture tests. In this study, the BI test system has been developed to evaluate material properties. Tensile tests, fracture toughness tests, hardness tests and BI tests were performed by the system using four classes of thermally aged specimens. The results of the BI tests were in good agreement with fracture characteristics from a standard fracture test method.