• 제목/요약/키워드: prediction horizon

검색결과 44건 처리시간 0.028초

적분 공정 제어를 위한 향상된 DMC (Improved DMC for the integrating process)

  • 강병삼;한종훈;장근수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.1120-1123
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    • 1996
  • DMC(Dynamic Matrix Control) algorithm has been successfully used in industries for more than a decade. It can handle constraints and easily extended to MIMO case. The application of DMC, however, is limited to the open loop stable process because it uses the FIR(Finite Impulse Response) or FSR(Finite Step Response) model. Integrating process widely used in chemical process industry, is the representative open loop unstable process. The disturbance rejection of DMC is relatively poor due to the assumption that the current disturbance is equivalent to the future disturbance. We propose the IDMC(Improved Dynamic Matrix Control) for the integrating process, as well as non-integrating process. IDMC has shown better disturbance rejection using multi-step ahead predictor for the disturbance.

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쌍일차 공정의 적응 예측제어 (An adaptive predictive control for the bilinear process)

  • 노균;윤인섭;여영구;송형근
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 26-27 Oct. 1990
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    • pp.344-349
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    • 1990
  • Under the assumption that process input/output data are sufficiently rich to allow reasonable plant identification, a long-range predictive control method for SISO bilinear plant is derived. In order to ensure offset-free behaviour of the control method, a new bilinear CARIMA model with variable dead-time is introduced. Furthermore, to extend the maximum output prediction horizon, the future predicted outputs in the bilinear term are assumed to be equal to the known future set-points. With a classical recursive adaptation algorithm, the proposed control scheme is capable of stable control of bilinear plants with variable parameters, with variable dead-time, and with a model order which changes instantaneously. Several simulation results demonstrate the characteristics of the proposed bilinear model predictive control method.

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Development of Real Coded Genetic Algorithm for Multiperiod Optimization

  • Chang, Young-Jung;Song, Sang-Ok;Song, Ji-Ho;Dongil Shin;S. Ando
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.396-396
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    • 2000
  • Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is tried. and many heuristics are adopted for this purpose.

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소결공장의 계산기 제어를 위한 새로운 제어 앨고리 (A New Control Algorithm for the Direct Digital Control Loops of Sintering Processes)

  • 권욱현;고명삼;이상정;김점근;백기남;김대원
    • 대한전기학회논문지
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    • 제36권1호
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    • pp.43-51
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    • 1987
  • In this paper, a state-space model of the burnthrough point control system of an industrial sintering process is derived. The model is then used in designing a self-tuning controller which consists of the receding horizon control law and a least-squares prediction algorithm with covariance resetting. By applying this controller to POSCO IV sintering process, satisfactory experimental results have been obtained. This paper presents some of these real-time experimental results and analyzes the control performance through productivity, operation indices, quality, sintered material composition, etc. From these experimental results and simulation results, the validity of the model can be observed. Moreover, the properties of the controller, e.g. stability, steady-state error, are shown based on the model.

Use of similarity indexes to identify spatial correlations of sodium void reactivity coefficients

  • Jimenez-Carrascosa, Antonio;Garcia-Herranz, Nuria
    • Nuclear Engineering and Technology
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    • 제52권11호
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    • pp.2442-2451
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    • 2020
  • The safety level of Sodium Fast Reactors is directly related with the sodium void reactivity. A low-void effect design has been proposed within the Horizon2020 ESFR-SMART project thanks to the introduction of a sodium plenum above the active core. In order to assess the impact of this core conception on transient analysis, a map with the spatial distribution of sodium void worth can be computed and fed into a point-kinetics-based transient code. Due to the spatial correlations between neighboring zones, the global effect of voiding two different axial or radial regions is not necessarily the sum of both individual contributions. Neglecting those correlations in the void worth map and consequently in the transient analysis may lead to an unrealistic prediction of the transient sequences. In this work, a method based on sensitivity analysis and similarity assessment is proposed for predicting those correlations. The method proved to be able to establish correlations between axial slices of a sub-assembly and was checked against realistic sodium void propagation patterns.

소셜 빅데이터 기반 공공정책 국민의견 수렴과 정책 시행 이후 결과 관계 분석: '복지' 정책 사례를 중심으로 (An Analysis of the Relationship between Public Opinion on Social Bigdata and Results after Implementation of Public Policies: A Case Study in 'Welfare' Policy)

  • 김태영;김용;오효정
    • 디지털융복합연구
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    • 제15권3호
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    • pp.17-25
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    • 2017
  • 슈 스캐닝은 미래예측을 위한 방법 중 하나로 정보화 시대의 큰 화두인 빅데이터에 기반한 미래예측에 적합한 방법이다. 이에 본 연구에서는 이슈 스캐닝 기법을 통해서 현재 우리 사회가 당면한 문제점들을 과학적으로 파악하고, 이를 해결할 수 있는 공공정책 수립에 기여하고자 한다. 효과적인 공공정책 수립을 위해서는 다양한 빅데이터 분석을 통해 국민이 정책에 대해 예측한 위험 및 기대요소를 파악해야 한다. 본 연구에서는 소셜 빅데이터를 기반으로 공공정책에 대한 국민의견 수렴 절차를 설계하고, 정책시행 이후 결과와의 비교 분석을 통해 공공정책에 대한 의견수렴이 정책 수립에 필요한 절차인지를 확인해 보았다. 연구 적용 대상 정책으로는 '만 0-5세 무상보육제'를 선정하였으며, 해당 정책에 대한 국민의 인식이 어떻게 나타나는지 소셜 빅데이터를 통해 분석함으로써 차후 정책 수립시 반영해야 할 시사점을 도출하였다. 본 연구를 통해 얻을 수 있는 시사점은 빅데이터를 활용하여 공공정책에 관한 국민 여론을 수렴하는 것은 정책수립 시에 매우 중요하며, 이는 전 국민이 필요로 하는 정책을 수립하고 사회 발전을 위한 국가적 차원의 대응체계 구축을 위한 밑거름이 될 수 있음에 있다.

제주지역 바람자료 분석 및 풍속 예측에 관한 연구 (A Study on the Wind Data Analysis and Wind Speed Forecasting in Jeju Area)

  • 박윤호;김경보;허수영;이영미;허종철
    • 한국태양에너지학회 논문집
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    • 제30권6호
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    • pp.66-72
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    • 2010
  • In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST~15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times(0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22~23%, increased gradually up to 25~29% for 48 hours predictions.

대규모 비선형 시스템의 새로운 계층별 최적제어 (A New Approach for Hierarchical Optimization of Large Scale Non-linear Systems)

  • 박준훈;김종부
    • 전자공학회논문지T
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    • 제36T권2호
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    • pp.21-31
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    • 1999
  • 대규모 시스템 제어와 관련하여 몇 개의 부시스템으로 분할하여 처리하는 계층별 제어이론이 많이 연구되어 왔으며 특히 치수가 높은 대규모 비선형 시스템의 경우에 고차의 비선형 미분방정식을 동시에 적분을 해야하고 많은 계산량을 필요로 하므로 해를 구하기가 어려운 문제가 있다. 1980년대 Singh과 Hassan은 상호예측 알고리즘(two level prediction algorithm)을 제시한바 있고 이 방법은 비선형 대규모 시스템의 최적제어에 효과적이나 시스템 행렬 Q, R, S, H에 따라 제한된 최적화 구간에서만 성립되는 등 최적화 구간의 길이와 수렴성 여부가 행렬 값에 영향을 받는 알고리즘상의 단점이 있다. 본 연구에서는 수렴조건으로부터 평가함수에 구속조건(quadratic penalty term)을 부여하지 않는 새로운 개선된 알고리즘을 제시 적용하여 시스템 행렬 결정을 위한 과정 없이 수렴속도의 향상과 함께 최적의 수렴성 및 최적화 구간을 얻도록 했다. 분할된 비선형 시스템의 최적제어를 위해서는, 대수 반복연산만으로 2점 경계치 문제(two point boundary value problem)를 해결함으로써 기존의 수치 해석법에 비해 연산이 간단한 블록펄스 변환 방법을 사용해서 처리했다.

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A cognitive model for forecasting progress of multiple disorders with time relationship

  • Kim, Soung-Hie;Park, Wonseek;Chae, In-Ho
    • 한국경영과학회:학술대회논문집
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    • 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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    • pp.505-510
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    • 1996
  • Many diseases cause other diseases with strength of influences and time intervals. Prognostic and therapeutic assessments are the important part of clinical medicine as well as diagnostic assessments. In cases where a patient already has manufestations of multiple disorders (complications), progress forecasting and therapy decision by physicians without support tools are very dificult: physicians often say that "Once complications set in, the patient may die". Treating complications are difficult tasks for physicians, because they have to consider all of the complexities, possibilities and interactions between the diseases. The prediction of multiple disorders has many bundles that arise from such time-dependent interrelationships between diseases and nonlinear progress. This paper proposes a model based on time-dependent influences, which appropriately describes the progress of mulitple disorders, and gives some modificaitons for applying this model to medical domains: time-dependent influence matrix manifestation vector, therapy efficacy matrix, S-shaped curve approximation, definitions of which are provided. This research proposes an algorithm for forecasting the state of each disease on the time horizon and for evaluation of therapy alternatives with not toy example, but real patient history of multiple disorders.disorders.

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Real-time Optimal Operation Planning of Isolated Microgrid Considering SOC balance of ESS

  • Lee, Yoon Cheol;Shim, Ji Yeon;Kim, Jeongmin;Ryu, Kwang Ryel
    • 한국컴퓨터정보학회논문지
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    • 제23권10호
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    • pp.57-63
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    • 2018
  • The operating system for an isolated microgrid, which is completely disconnected from the central power system, aims at preventing blackouts and minimizing power generation costs of diesel generators through efficient operation of the energy storage system (ESS) that stores energy produced by renewable energy generators and diesel generators. In this paper, we predict the amount of renewable energy generation using the weather forecast and build an optimal diesel power generation plan using a genetic algorithm. In order to avoid inefficiency due to inaccurate prediction of renewable energy generation, our search algorithm imposes penalty on candidate diesel power generation plans that fail to maintain the SOC (state of charge) of ESS at an appropriate level. Simulation experiments show that our optimization method for maintaining an appropriate SOC balance can prevent the blackout better when compared with the previous method.