• 대한산업공학회지
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• 제29권4호
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• pp.304-311
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• 2003

This paper considers a new variation of scheduling problems where jobs are dispatched in batches. The variation is the case where the batch sequence is fixed. The objective is to minimize the sum of the completion times of the batches. This simple environment has a variety of real world applications such as part kitting and customer order scheduling. We show that this problem is binary NP-complete when there exist two machines. For the same problem, we develop an optimal dynamic programming (DP) algorithm which runs in pseudo-polynomial time. We finally prove the optimality of the DP algorithm.

• 한국수자원학회논문집
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• 제43권1호
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• pp.67-79
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• 2010

한국수자원공사는 낙동강 및 금강수계에 대해 실시간 물관리 시스템을 개발하여 수계 내 다목적 댐의 효율적인 운영을 도모하였다. 본 연구에서는 이를 확장하여 최적화 기법인 표본 추계학적 동적계획법을 사용하여 한강수계 다목적댐의 효율적인 월말 목표저수량을 산정하고 이를 통해 실시간 물관리시스템의 효율을 극대화하고자 수행되었다. 수계 내 댐중 저수용량과 용수공급 측면에서 중요도가 높은 소양강댐, 충주댐, 화천댐 등 3개 댐만을 대상으로 모형을 개발하였으며 저수량 상태변수의 민감도 분석 결과를 통해 저수량 상태변수 개수를 설정하였다. 본 연구를 통해 제시된 최적화모형을 통한 운영률과 한국수자원공사의 운영목표수위에 의한 저수지 운영방식과 비교를 실시한 결과 연평균 37.22 MCM의 수계 내 요구용수 부족량 감소효과와 더불어 발전량 측면에서도 연간 171 GWh가 증가하는 것을 확인하였다. 또한 이수기 저수지 운영계획 시스템을 실제 적용한 결과 2007년~2008년 이수기 동안 전력생산, 수질개선 등을 위한 추가적인 용수공급이 가능하다는 것을 확인하였다. 이러한 실제 적용사례를 통해 SSDP 모형과 이수기 저수지운영 시스템의 그 유용성을 타진할 수 있었으며 다른 수계로 확장을 실시한다면 보다 합리적인 저수지 운영계획이 가능할 것으로 기대한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.570-574
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• 1990

Detection of left ventricular boundary for the functional analysis of LV(left ventricle)is obtained using automatic boundary detection algorithm based on dynamic programming method. This scheme reduces the edge searching time and ensures connective edge detection, since it does not require general edge operator, edge thresholding and linking process of other edge. detection methods. The left ventricular diastolic volume and systolic volume and systolic volume were computed after this automatic boundary detection, and these Volume data wm applied to analyze LV ejection fraction.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2007년도 추계학술대회 논문집
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• pp.508-509
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• 2007

For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates.

• Nuclear Engineering and Technology
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• 제55권8호
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• pp.2952-2965
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• 2023

Advanced reactors, such as Small Modular Reactors or existing Nuclear Power Plants, often use Field Programmable Gate Array (FPGA) based controllers in new Instrumentation and Control (I&C) system architectures or as an alternative to existing analog-based I&C systems. Compared to CPU-based Programmable Logic Controllers (PLCs), FPGAs offer better overall performance. However, programming functions on FPGAs can be challenging due to the requirement for a hardware description language that does not explicitly support the operation of real numbers. This study aims to implement the Reactor Trip (RT) functions of the existing analog-based Reactor Protection System (RPS) using FPGAs. The RT equations for Overtemperature delta Temperature and Overpower delta Temperature involve dynamic compensators expressed with the Laplace transform variable, 's', which is not directly supported by FPGAs. To address this issue, the trip equations with the Laplace variable in the continuous-time domain are transformed to the discrete-time domain using the Z-transform. Additionally, a new operation based on a relative value for the equation range is introduced for the handling of real numbers in the RT functions. The proposed approach can be utilized for upgrading the existing analog-based RPS as well as digitalizing control systems in advanced reactor systems.

• 한국콘텐츠학회논문지
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• 제7권6호
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• pp.44-51
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• 2007

원격지 모형 물체에 대한 추출정보의 실시간 정보의 인식 및 전송을 위하여 실시간 신경회로망을 제안하였다. 제시된 신경회로망 기법은 내부 노드의 확산을 통하여 실시간 계산 기법으로 수행된다. 회로망 내에서 노드는 양자화 된 입력 영역내의 한 상태로 결정되며, 각 노드는 자신의 입력신호와 이웃하는 정보입력의 가중치 신호의 합에 의해 새로운 정보 유닛으로 산출되어진다. 모형 물체의 실시간 인식을 위하여 제안되는 가장 이상적인 알고리즘은 순서적 정합기법인데, 임의의 위치 정보를 주변의 상태 공간에 신속하게 전파시켜 자연스런 정보의 보간 상태를 이룬다. 비선형 불규칙적 영상정보를 실시간인식을 위하여 다양한 시뮬레이션을 실행하였다. 1차원 정보전파 신경망 하드웨어를 제작하여 정적 및 동적 신호가 있는 다양한 실험을 수행하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.620-626
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• 2004

For general nonlinear processes, it is difficult to control with a linear model-based control method and nonlinear controls are considered. Among the numerous approaches suggested, the most rigorous approach is to use dynamic optimization. Many general engineering problems like control, scheduling, planning etc. are expressed by functional optimization problem and most of them can be changed into dynamic programming (DP) problems. However the DP problems are used in just few cases because as the size of the problem grows, the dynamic programming approach is suffered from the burden of calculation which is called as 'curse of dimensionality'. In order to avoid this problem, the Neuro-Dynamic Programming (NDP) approach is proposed by Bertsekas and Tsitsiklis (1996). To get the solution of seriously nonlinear process control, the interest in NDP approach is enlarged and NDP algorithm is applied to diverse areas such as retailing, finance, inventory management, communication networks, etc. and it has been extended to chemical engineering parts. In the NDP approach, we select the optimal control input policy to minimize the value of cost which is calculated by the sum of current stage cost and future stages cost starting from the next state. The cost value is related with a weight square sum of error and input movement. During the calculation of optimal input policy, if the approximate cost function by using simulation data is utilized with Bellman iteration, the burden of calculation can be relieved and the curse of dimensionality problem of DP can be overcome. It is very important issue how to construct the cost-to-go function which has a good approximate performance. The neural network is one of the eager learning methods and it works as a global approximator to cost-to-go function. In this algorithm, the training of neural network is important and difficult part, and it gives significant effect on the performance of control. To avoid the difficulty in neural network training, the lazy learning method like k-nearest neighbor method can be exploited. The training is unnecessary for this method but requires more computation time and greater data storage. The pH neutralization process has long been taken as a representative benchmark problem of nonlin ar chemical process control due to its nonlinearity and time-varying nature. In this study, the NDP algorithm was applied to pH neutralization process. At first, the pH neutralization process control to use NDP algorithm was performed through simulations with various approximators. The global and local approximators are used for NDP calculation. After that, the verification of NDP in real system was made by pH neutralization experiment. The control results by NDP algorithm was compared with those by the PI controller which is traditionally used, in both simulations and experiments. From the comparison of results, the control by NDP algorithm showed faster and better control performance than PI controller. In addition to that, the control by NDP algorithm showed the good results when it applied to the cases with disturbances and multiple set point changes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.805-812
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• 1989

An efficient diagnostic approach for real-time operation aiding expert system in chemical process plants is discussed. The approach is based on the hybrid of the simplified symptom tree(SST) and the fault consequence digraph(FCD), representation of propagation patterns of fault states. The SST generates fault hypothesis efficiently and the FCD resolve the real fault accurately. Frame based knowledge representation and object-oriented programming make diagnostic system general and efficient. Truth maintenance system enables robust pattern matching and provides enhanced explain facilities. A prototype expert system for supports operation of naphtha furnaces process, called OASYS, has been built and tested to demonstrate this methodology. Utilization of diversified process symbolic data, produced using dynamic normal standards, overcomes the problem of qualitative Boolean reasoning and enhance the applicability.

• 대한토목학회논문집
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• 제8권1호
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• pp.49-60
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• 1988

낙동강 수계의 남강(南江)-안동(安東)댐군(群)을 하나의(가상적) 시스템으로 간주하여 홍수시 두 댐 하류의 합류점에서의 최대 유량을 최소로하기 위한 min-max IDP(Incremental Dynamic Programming) 모델을 수립하였다. 200년 반도의 예촉유입홍수량에 대하여 분석한 결과, 단일댐운영 방식에 의한 홍수조절보다 댐군(群)을 시스템적 관점에서 최적화 과정에 의한 홍수조절(洪水調節)을 하는 것이 효율적임을 수치적으로 입증하였다.

• 대한기계학회논문집A
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• 제21권1호
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• pp.62-72
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• 1997

High flexibility and productivity using industrial robots are being achieved in manufacturing lines with off-line robot programmings. A good off-line programming system should have functions of robot modelling, trajectory planning, graphical teach-in, kinematic and dynamic simulations. Simulated results, however, can hardly be applied to on-line tasks until any calibration procedure is accompained. This paper proposes a visual calibration scheme in order to provide a calibration tool for our own off-line programming system of SCARA robots. The suggested scheme is based on the position-based visual servoings, and the perspective projection. The scheme requires only one camera as it uses saved kinematic data for three-dimensional visual calibration. Predicted images are generated and then compared with camera images for updating positions and orientations of objects. The scheme is simple and effective enough to be used in real time robot programming.