• Title/Summary/Keyword: Off-line simulation

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Study on the micro-scale simulation of wind field over complex terrain by RAMS/FLUENT modeling system

  • Li, Lei;Zhang, Li-Jie;Zhang, Ning;Hu, Fei;Jiang, Yin;Xuan, Chun-Yi;Jiang, Wei-Mei
    • Wind and Structures
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    • v.13 no.6
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    • pp.519-528
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    • 2010
  • A meteorological model, RAMS, and a commercial computational fluid dynamics (CFD) model, FLUENT are combined as a one-way off-line nested modeling system, namely, RAMS/FLUENT system. The system is experimentally applied in the wind simulation over a complex terrain, with which numerical simulations of wind field over Foyeding weather station located in the northwest mountainous area of Beijing metropolis are performed. The results show that the method of combining a meteorological model and a CFD model as a modeling system is reasonable. In RAMS/FLUENT system, more realistic boundary conditions are provided for FLUENT rather than idealized vertical wind profiles, and the finite volume method (FVM) of FLUENT ensures the capability of the modeling system on describing complex terrain in the simulation. Thus, RAMS/FLUENT can provide fine-scale realistic wind data over complex terrains.

INTEGRATED DEVELOPMENT ENVIRONMENT FROM MODELING TO IMPLEMENTATION FOR AUTOMOTIVE REAL-TIME EMBEDDED CONTROL SYSTEMS

  • Ma, J.;Youn, J.;Shin, M.;Hwang, I.;SunWoo, M.
    • International Journal of Automotive Technology
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    • v.7 no.3
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    • pp.345-351
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    • 2006
  • Software-In-the-Loop Simulation(SILS) and Rapid Control Prototyping(RCP) are proposed as an integrated development environment to support the development process from system design to implementation. SILS is an environment used to simulate control systems with temporal behavior. RCP offers seamless phase shift from design to implementation based on automatic code generation. There are several toolsets that support control system design and analysis. A few of these tools generate the control software automatically. However, most of these design toolsets do not cover temporal behavior which appears after implementation. In earlier toolsets, the design and the implementation of a control system are considered as two separate processes which mean the conventional development process is not connected strictly. SILS/RCP environments work under an identical platform and use the same representation for system modeling. An integrated SILS/RCP environment makes it possible to design controllers under conditions similar to real execution during off-line simulation and to realize controllers in the early design phase. SILS/RCP environments integrate the design and implementation phases which reduce the time-to-market and provide greater performance-assured design. The establishment of SILS/RCP and the practical design approaches are presented.

Software Sensing for Glucose Concentration in Industrial Antibiotic Fed-batch Culture Using Fuzzy Neural Network

  • Imanishi, Toshiaki;Hanai, Taizo;Aoyagi, Ichiro;Uemura, Jun;Araki, Katsuhiro;Yoshimoto, Hiroshi;Harima, Takeshi;Honda , Hiroyuki;Kobayashi, Takeshi
    • Biotechnology and Bioprocess Engineering:BBE
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    • v.7 no.5
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    • pp.275-280
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    • 2002
  • In order to control glucose concentration during fed-batch culture for antibiotic production, we applied so called “software sensor” which estimates unmeasured variable of interest from measured process variables using software. All data for analysis were collected from industrial scale cultures in a pharmaceutical company. First, we constructed an estimation model for glucose feed rate to keep glucose concentration at target value. In actual fed-batch culture, glucose concentration was kept at relatively high and measured once a day, and the glucose feed rate until the next measurement time was determined by an expert worker based on the actual consumption rate. Fuzzy neural network (FNN) was applied to construct the estimation model. From the simulation results using this model, the average error for glucose concentration was 0.88 g/L. The FNN model was also applied for a special culture to keep glucose concentration at low level. Selecting the optimal input variables, it was possible to simulate the culture with a low glucose concentration from the data sets of relatively high glucose concentration. Next, a simulation model to estimate time course of glucose concentration during one day was constructed using the on-line measurable process variables, since glucose concentration was only measured off-line once a day. Here, the recursive fuzzy neural network (RFNN) was applied for the simulation model. As the result of the simulation, average error of RFNN model was 0.91 g/L and this model was found to be useful to supervise the fed-batch culture.

A Study on Adaptive Control of AGV using Immune Algorithm (면역알고리즘을 이용한 AGV의 적응제어에 관한 연구)

  • 이영진;최성욱;손주한;이진우;조현철;이권순
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2000.04a
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    • pp.56-63
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    • 2000
  • Abstract - In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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A Study on Driving Control of an Autonomous Guided Vehicle using Humoral Immune Algorithm Adaptive PID Controller based on Neural Network Identifier Technique (신경회로망 동정기법에 기초한 HIA 적응 PID 제어기를 이용한 AGV의 주행제어에 관한 연구)

  • Lee Young Jin;Suh Jin Ho;Lee Kwon Soon
    • Journal of the Korean Society for Precision Engineering
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    • v.21 no.10
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    • pp.65-77
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    • 2004
  • In this paper, we propose an adaptive mechanism based on immune algorithm and neural network identifier technique. It is also applied fur an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To solve this problem, we use the neural network identifier (NNI) technique fur modeling the plant and humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using an immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. Finally, the simulation and experimental result fur the control of steering and speed of AGV system illustrate the validity of the proposed control scheme. These results for the proposed method also show that it has better performance than other conventional controller design methods.

Possibilities and Limitations of E-learning in Medical Education (의학교육에 있어서 이러닝(e-learning)의 가능성과 한계)

  • Im, Eun-Jung
    • Korean Medical Education Review
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    • v.11 no.1
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    • pp.21-33
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    • 2009
  • The purpose of this study is to review a variety of e-learning use in medical education, and to analyze the e-learning related research in medical education, finally to discuss possibilities and limitations of e-learning in future. Subjects of this research are 46 papers published in Korean Medical Database, PubMed, MEDLIS, RISS4U. Content analysis of 46 papers have been conducted based on the period of research, research methods, research subjects, study personnel, effectiveness. The results are as follows. First, various e-learning, such as hyper-media, simulation-based medical education (SBME), game-based learning, web-based learning, computer-based test (CBT) are implemented in medical education. Second, 35 research (76.1%) has verified the positive effect of e-learning. Third, in the case of Korean studies, experimental studies (46.2%) in a short period (46.2%) of 50-100 people (42.3%) to take the most. As a result, it is reported a lack of theoretical discussion and insight on e-learning compared to foreign research. Educational paradigms are currently shifting from off-line to on-line, from traditional classroom lecture to e-learning. But e-learning is not a substitution to traditional teaching, but a matter of choice. The choice is up to medical professors and students.

A Study on an AVR Parameter Tuning Method using Real-lime Simulator (실시간 시뮬레이터를 이용한 AVR의 파라미터 튜닝에 관한 연구)

  • Kim, Jung-Mun;Mun, Seung-Il
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.2
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    • pp.69-75
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    • 2002
  • AVR parameter tuning for voltage control of power system generators has generally been performed with the analytic methods and the simulation methods, which mostly depend on off-line linear mathematical models of excitation control system. However, due to the nonlinear nature of excitation control system, excitation control system performance of the tuned Parameters using the above conventional tuning methods may not be appropriate for some operating conditions. This paper presents an AVR parameter tuning method using actual on-line data of the excitation control system with the parameter optimization technique. As this method utilizes on-line operating data of the target excitation control system not the mathematical model of the system, it can overcome the limitation of model uncertainty Problems in conventional method, and it can tune the AVR parameter set which gives desired performance at the operating conditions. For the verification of proposed tuning method, two case studies with scaled excitation systems and the real-time power system simulator are presented.

An AGV Driving Control using immune Algorithm Adaptive Controller (면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, Yeong-Jin;Lee, Gwon-Sun;Lee, Jang-Myeong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.4
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    • pp.201-212
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    • 2000
  • In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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Performance Improvement on MPLS On-line Routing Algorithm for Dynamic Unbalanced Traffic Load

  • Sa-Ngiamsak, Wisitsak;Sombatsakulkit, Ekanun;Varakulsiripunth, Ruttikorn
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1846-1850
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    • 2005
  • This paper presents a constrained-based routing (CBR) algorithm called, Dynamic Possible Path per Link (D-PPL) routing algorithm, for MultiProtocol Label Switching (MPLS) networks. In MPLS on-line routing, future traffics are unknown and network resource is limited. Therefore many routing algorithms such as Minimum Hop Algorithm (MHA), Widest Shortest Path (WSP), Dynamic Link Weight (DLW), Minimum Interference Routing Algorithm (MIRA), Profiled-Based Routing (PBR), Possible Path per Link (PPL) and Residual bandwidth integrated - Possible Path per Link (R-PPL) are proposed in order to improve network throughput and reduce rejection probability. MIRA is the first algorithm that introduces interference level avoidance between source-destination node pairs by integrating topology information or address of source-destination node pairs into the routing calculation. From its results, MIRA improves lower rejection probability performance. Nevertheless, MIRA suffer from its high routing complexity which could be considered as NP-Complete problem. In PBR, complexity of on-line routing is reduced comparing to those of MIRA, because link weights are off-line calculated by statistical profile of history traffics. However, because of dynamic of traffic nature, PBR maybe unsuitable for MPLS on-line routing. Also, both PPL and R-PPL routing algorithm we formerly proposed, are algorithms that achieve reduction of interference level among source-destination node pairs, rejection probability and routing complexity. Again, those previously proposed algorithms do not take into account the dynamic nature of traffic load. In fact, future traffics are unknown, but, amount of previous traffic over link can be measured. Therefore, this is the motivation of our proposed algorithm, the D-PPL. The D-PPL algorithm is improved based on the R-PPL routing algorithm by integrating traffic-per-link parameters. The parameters are periodically updated and are dynamically changed depended on current incoming traffic. The D-PPL tries to reserve residual bandwidth to service future request by avoid routing through those high traffic-per-link parameters. We have developed extensive MATLAB simulator to evaluate performance of the D-PPL. From simulation results, the D-PPL improves performance of MPLS on-line routing in terms of rejection probability and total throughput.

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Pipelined Wake-Up Scheme to Reduce Power-Line Noise of MTCMOS Megablock Shutdown for Low-Power VLSI Systems (저전력 VLSI 시스템에서 MTCMOS 블록 전원 차단 시의 전원신 잡음을 줄인 파이프라인 전원 복귀 기법)

  • 이성주;연규성;전치훈;장용주;조지연;위재경
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.41 no.10
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    • pp.77-83
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    • 2004
  • In low-power VLSI systems, it is effective to suppress leakage current by shutting down megablocks in idle states. Recently, multi-threshold voltage CMOS (MTCMOS) is widely accepted to shutdown power supply. However, it requires short wake-up time as operating frequency increases. This causes large current surge during wake-up process, and it often leads to system malfunction due to severe Power line noise. In this paper, a novel wake-up scheme is proposed to solve this problem. It exploits pipelined wake-up strategy in several stages that reduces maximum current on the power line and its corresponding power line noise. To evaluate its efficiency, the proposed scheme was applied to a multiplier block in the Compact Flash memory controller chip. Power line noise in shutdown and wake-up process was simulated and analyzed. From the simulation results, the proposed scheme was proven to greatly reduce the power line noise compared with conventional schemes.