• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.4 s.310
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• pp.35-44
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• 2006

The network induced transmission delay deteriorates the performance and stability of the real-time distributed control system on LonWorks over IP (LonWorks/IP) virtual device network (VDN). LonWorks/IP virtual device network is an integrated form of LonWorks device network and IP data network. The time delay in servo control on the LonWorks/IP-based VDN has highly stochastic nature. In the real-time distributed servo applications for predictive maintenance on the factory floor, timely response is essential.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.503-515
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• 2022

The permeability coefficient is an essential parameter for the study of seepage flow in fractured rock mass. This paper discusses the feasibility and application value of using readily available RQD (rock quality index) data to estimate mine water inflow and grouting quantity. Firstly, the influence of different fracture frequencies on permeability in a unit area was explored by combining numerical simulation and experiment, and the relationship between fracture frequencies and pressure and flow velocity at the monitoring point in fractured rock mass was obtained. Then, the stochastic function generation program was used to establish the flow analysis model in fractured rock mass to explore the relationship between flow velocity, pressure and analyze the universal law between fracture frequency and permeability. The concepts of fracture width and connectivity are introduced to modify the permeability calculation formula and grouting formula. Finally, based on the on-site grouting water control example, the rock mass quality index is used to estimate the mine water inflow and the grouting quantity. The results show that it is feasible to estimate the fracture frequency and then calculate the permeability coefficient by RQD. The relationship between fracture frequency and RQD is in accordance with exponential function, and the relationship between structure surface frequency and permeability is also in accordance with exponential function. The calculation results are in good agreement with the field monitoring results, which verifies the rationality of the calculation method. The relationship between the rock mass RQD index and the rock mass permeability established in this paper can be used to invert the mechanical parameters of the rock mass or to judge the permeability and safety of the rock mass by using the mechanical parameters of the rock mass, which is of great significance to the prediction of mine water inflow and the safety evaluation of water inrush disaster management.

• Korean Journal of Optics and Photonics
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• v.34 no.1
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• pp.1-12
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• 2023

In this study, we propose a hybrid phase-control algorithm for multi-channel coherent beam combining (CBC) system by combining the covariant matrix adaption evolution strategy (CMA-ES) and stochastic parallel gradient descent (SPGD) algorithms and analyze its operational performance. The proposed hybrid CMA-ES/SPGD algorithm is a sequential process which initially runs the CMA-ES algorithm until the combined final output intensity reaches a preset interim value, and then switches to running the SPGD algorithm to the end of the whole process. For ideal 7-channel and 19-channel all-fiber-based CBC systems, we have found that the mean convergence time can be reduced by about 10% in comparison with the case when the SPGD algorithm is implemented alone. Furthermore, we analyzed a more realistic situation in which some additional phase noise was introduced in the same CBC system. As a result, it is shown that the proposed algorithm reduces the mean convergence time by about 17% for a 7-channel CBC system and 16-27% for a 19-channel system compared to the existing SPGD alone algorithm. We expect that for implementing a CBC system in a real outdoor environment where phase noise cannot be ignored, the hybrid CMA-ES/SPGD algorithm proposed in this study will be exploited very usefully.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.12
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• pp.529-538
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• 2002

Conventional method to reduce the handoff call blocking probability(PBH) in mobile communication system is to reserve a predetermined number of channels only for handoff calls. To determine the number of reserved channels, an optimization problem, which is generally computationally heavily involved, must be solved. In this Paper, we propose a call admission control (CAC) scheme that can be used to reduce the PBH without reserving channels in advance. For this, we define a new measure, gain, which depends on the state of the system upon the arrival of a new call. The proposed CAC decision rule relies on the gain computed when a new call arrives. SRN, an extended stochastic Petri nets, provides compact modeling facilities for system analysis can be calculated performance index by appropriate reward to the model. In this Paper, we develop SRN models which can perform the CAC with gain. The SRN models are 2 level hierarchical models. The upper layer models are the structure state model representing the CAC and channel allocation methods considering QoS with multimedia traffic The lower layer model Is to compute the gain under the state of the upper layer models.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.2
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• pp.100-106
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• 2014

Lower control arm (LCA) is a part of chassis in automotive. Performances of LCA such as stiffness, durability and permanent displacement must be considered in design optimization. However it is hard to consider different performances at once in optimization because these are measured by different commercial tools like Radioss, Abaqus, etc. In this paper, firstly, we construct the integrated design automation system for LCA based on Matlab including Hypermesh, Radioss and Abaqus. Secondly, Akaike information criterion (AIC) is used for assessment of reliability of LCA. It can find the best estimated distribution of performance from limited and discrete stochastic information and then obtains the reliability from the distribution. Finally, we consider tolerances of design variables and variation of elastic modulus and achieve the target reliability by carrying out reliability-based design optimization (RBDO) with the integrated system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.451-463
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• 2007

This paper describes issues of GPS network adjustment to determine coordinate sets of the $2^{nd}$ order national geodetic control points based on the Korean Geodetic Datum (KGD2002) which has been newly adopted in 2003, After outlining theoretical background of the GPS network processing, the adjustment procedure applied for this project is detailed. Throughout performing a series of minimally constrained adjustments, some outliers have been removed and magnitude of absolute and relative error for a stochastic modeling has been determined as 4mm+0.4ppm and 8mm+0.8ppm in the horizontal and vertical component, respectively. The over constrained adjustment by fixing the $1^{st}$ order control points was performed to derive final solution, indicating that the accuracy of the estimated coordinates was 2cm and 4cm in the horizontal and vertical component.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.4
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• pp.118-125
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• 2012

When monitoring an instrumental process, one often collects a host of data such as characteristic signals sent by a sensor in short time intervals. Characteristic data of short time intervals tend to be autocorrelated. In the instrumental processes often the practice of adjusting the setting value simply based on the previous one, so-called 'adjacent point operation', becomes more critical, since in the short run the deviations are harder to detect and in the long run they have amplified consequences. Stochastic modelling using ARIMA or AR models are not readily usable here. Due to the difficulty of dealing with autocorrelated data conventional practice is resorting to choosing the time interval where autocorrelation is weak enough then to using I-MR control chart to judge the process stability. In the autocorrelated instrumental processes it appears that using the Shewhart chart and the time interval data where autocorrelation is relatively not existent turns out to be a rather convenient and very useful practice to determine the process stability. However in the autocorrelated instrumental processes we intend to show that one would presumably do better using the EWMA control chart rather than just using the Shewhart chart along with some arbitrarily intervalled data, since the former is more sensitive to shifts given appropriate weights.

• Journal of the Korea Society of Computer and Information
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• v.12 no.5
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• pp.273-284
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• 2007

This paper studies a periodic review inventory model with an e-MarketPlace transaction in reconfigurable manufacturing system(RMS). A decision maker can expand/reduce production capacity/quantities and/or replenish/dispose inventories from/to e-MarketPlace urgently to satisfy the stochastic demands. If inventories are replenished or disposed through e-MarketPlace, this leadtime is shorter than the production leadtime, but unit purchasing or selling cost is more expensive than that of expanding capacity or reducing production quantities respectively. Henceforth, trade-off on these alternatives is considered. In addition to this, in order to consider the economy of scale, our model includes the fixed cost for purchasing from e-MarketPlace and capacity expansion. We use dynamic programming and K convexity methods to characterize the nature of the optimal policy. Finally, We present the optimal inventory control policy which is composed by the combinations of a base stock and (s,S) type policy.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.138-141
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• 2003

Recently reinforcement learning has attracted attention of many researchers because of its simple and flexible learning ability for any environments. And so far many reinforcement learning methods have been proposed such as Q-learning, actor-critic, stochastic gradient ascent method and so on. The reinforcement learning system is able to adapt to changes of the environment because of the mutual action with it. However when the environment changes periodically, it is not able to adapt to its change well. In this paper we propose the reinforcement learning system that is able to adapt to periodical changes of the environment by introducing the time-varying parameters to be adjusted. It is shown that the proposed method works well through the simulation study of the maze problem with aisle that opens and closes periodically, although the conventional method with constant parameters to be adjusted does not works well in such environment.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.11-18
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• 2017

In order to maintain customer voltages within the allowable limit($220{\pm}13V$) as much as possible, tap operation strategy of SVR(Step Voltage Regulator) which is located in primary feeder, is widely used for voltage control in the utilities. However, SVR in nature has operation characteristic of the delay time ranging from 30 to 150 sec, and then the compensation of BESS (Battery Energy Storage System) during the delay time is being required because the customer voltages in distribution system may violate the allowable limit during the delay time of SVR. Furthermore, interconnection of PV(Photovoltaic) system could make a difficultly to keep customer voltage within the allowable limit. Therefore, this paper presents an optimal coordination operation algorithm between BESS and SVR based on a conventional LDC (Line Drop Compensation) method which is decided by stochastic approach. Through the modeling of SVR and BESS using the PSCAD/EMTDC, it is confirmed that customer voltages in distribution system can be maintained within the allowable limit.