• 한국물환경학회지
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• 제24권1호
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• pp.91-98
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• 2008

This work was performed to develop a model possible to predict the influent flow and influent components, which are one of main disturbances causing process problems at the operation of municipal wastewater treatment plant. In this study, artificial neural network (ANN) was used in order to develop a model that was able to predict the influent flow, $COD_{Mn}$, SS, TN 1 day-ahead, 2day-ahead and 3 day ahead. Multi-layer feed-forward back-propagation network was chosen as neural network type, and tanh-sigmoid function was used as activation function to transport signal at the neural network. And Levenberg-Marquart (LM) algorithm was used as learning algorithm to train neural network. Among 420 data sets except missing data, which were collected between 2005 and 2006 at field plant, 210 data sets were used for training, and other 210 data sets were used for validation. As result of it, ANN model for predicting the influent flow and components 1-3day ahead could be developed successfully. It is expected that this developed model can be practically used as follows: Detecting the fault related to effluent concentration that can be happened in the future by combining with other models to predict process performance in advance, and minimization of the process fault through the establishment of various control strategies based on the detection result.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.452-459
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• 2023

The core power control is an important issue for the study of dynamic characteristics in China initiative accelerator driven subcritical system (CiADS), which has direct impact on the control strategy and safety analysis process. The CiADS is an experimental facility that is only controlled by the proton beam intensity without considering the control rods in the current engineering design stage. In order to get the optimized operation scheme with the stable and reliable features, the variation of beam intensity using the continuous and periodic control approaches has been adopted, and the change of collimator and the adjusting of duty ratio have been proposed in the power control process. Considering the neutronics and the thermal-hydraulics characteristics in CiADS, the physical model for the core power control has been established by means of the point reactor kinetics method and the lumped parameter method. Moreover, the multi-inputs single-output (MISO) logical structure for the power control process has been constructed using proportional integral derivative (PID) controller, and the meta-heuristic algorithm has been employed to obtain the global optimized parameters for the stable running mode without producing large perturbations. Finally, the verification and validation of the control method have been tested based on the reference scenarios in considering the disturbances of spallation neutron source and inlet temperature respectively, where all the numerical results reveal that the optimization method has satisfactory performance in the CiADS core power control scenarios.

• 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.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.486-493
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• 2017

Refineries and chemical plants with isolated power systems that have a limited power supply are more susceptible to voltage changes from disturbances compared to power systems connected with a power company. Furthermore, most loads in such cases are induction motor loads, and therefore, transient voltage characteristics when starting a high-capacity motor must be examined. In general, high-capacity motors are customized appropriately to the load performance curve by the manufacturer during the construction of an industrial plant. Subsequently, when complying with the voltage drop permitted by international standards during the design process, power supply equipment such as transformers and generators is overdesigned. Therefore, a novel analysis is necessary on standards for startup and constraint voltage drops, as well as on identifying the voltage drop limitations for starting high-capacity motors in refineries and chemical plants with isolated power systems. In this study, field tests on an industrial plant were conducted, and simulations modeled under conditions identical to those of the field test system were performed using the general-purpose program ETAP in order to compare the results.

• 대한전기학회논문지:전력기술부문A
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• 제48권12호
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• pp.1479-1485
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• 1999

This paper proposes a fuzzy decision making method for power transformer protection to identify an internal fault from other transient states such as inrush, over-excitation and an external fault with current transformer (CT) saturation. In this paper, analyzing over 300 EMTP simulations of disturbances, four input variables are selected and fuzzified. At every sampling interval from half to one cycle after a disturbance, from the EMPT simulations, different fuzzy rule base is composed of twelve if-then fuzzy rules associated with their basic probability assignments for singleton- or compound-support hypotheses. Dempster's rule of combination is used to process the fuzzy rules and get the final decision. A series of test results clearly indicate that the method can identify not only an internal fault but also the other transients. The average of relay operation times is about 12(ms). The proposed method is implemented into a Digital Signal Processor (TMS320C31) and tested.

• Journal of Ecology and Environment
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• 제34권2호
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• pp.237-249
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• 2011

Land-use changes due to the socio-economic environment influence landscape patterns and processes, which affect habitats and biodiversity. This study considers the effects of such land-use changes, particularly on the traditional rural "Maeul" forested landscape, by analyzing landscape structure and vegetation changes. Three study areas were examined that have seen their populations decrease and age over the last few decades. Five types of plant life-forms (Raunkier life-forms) were distinguished to investigate ecosystem function. Principle component analysis was used to understand vegetation dynamics and community characteristics based on a vegetation similarity index. Ordination analysis transformed species-coverage data was introduced to clarify vegetation dynamics. Landscape indices, such as area metrics, edge metrics, and shape metrics, showed that spatial heterogeneity has increased over time in all areas. Pinus densiflora was the main land-use plant type in all study areas but decreased over time, whereas Quercus spp. increased. Over a decade, P. densiflora communities shifted to deciduous oak and plantation. These findings indicate that the impact of human activities on the Maeul landscape is twofold. While forestry activities caused heavy disturbances, the abandonment of traditional human activities has led to natural succession. Furthermore, it can be concluded that the type and intensity of these human impacts on landscape heterogeneity relate differently to vegetation succession. This reflects the cause and consequence of patch dynamics. We discuss an approach for sustainable landscape planning and management of the Maeul landscape based on traditional management.

• 대한기계학회논문집A
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• 제26권6호
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• pp.1092-1098
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• 2002

This paper discusses the composition of the theory of reinforcement teaming, which is applied in real-time teaming, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line teaming method. The individuals are reduced in order to team the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It is possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because of the teaming process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.

• 대한기계학회논문집A
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• 제21권3호
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• pp.502-510
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• 1997

A disturbance rejection controller using eccentricity filtering and LQ control techniques is proposed to alleviate the effecto of major roll eccentricity in multivariable cold-rolling processes. Fundamental problems in multivariable cold-rolling processes such as process time delay inherent in exit thickness measurement and non-stationary characteristics of roll eccentricity signals can be overcome by the proposed control method. The filtered instantaneous estimate of roll eccentricity may be exploited to improve instantaneous estimate of the exit thickness variation based on roll force and roll gap measurements, and a feedforward compensator is augmented as a reference for a gaugemeter thickness estimator. LQ feedback controller is combined with eccentricity filter for the attenuation of the exit thickness variation due to the entry thickness variation. The simulation results show that the roll eccentricity disturbance is significantly eliminated and other disturbances also are attenuated.

• 대한기계학회논문집B
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• 제27권2호
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• pp.243-250
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• 2003

The extinction behavior and the unsteady response of augmented reduced mechanism(ARM) have been investigated by adopting an OPPDIF code and a numerical solver for the flamelet equations. By comparing the performance of the ARM based on Miller and Bowman's mechanism(MB-ARM) with that of the ARM based on GRI-Mech 3.0(GRI-3.0-ARM), it is identified that the MB-ARM is more suitable for the unsteady calculation because it is relatively less stiff than GRI-3.0-ARM during an ignition process. The steady results using the MB-ARM, which is modified to predict reasonably the extinction point of experiment, are in excellent agreement with those from full mechanism. Under the sinusoidal transient disturbances of scalar dissipation rate, the unsteady responses of the flame temperature and species concentrations using a modified MB-ARM show in very close agreement with those from full mechanism. It is presumed that above modified MB-ARM is very suitable for the unsteady simulation of turbulent flames because it gives not only a low computational cost but also a good prediction performance for flame structure, extinction point and unsteady response.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.23-26
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• 2004

Recently, most of countries in the world are investing huge amount of capital for the infrastructure of logistics and trying to gain dominating position in logistics. To play the role of important hub in logistics, an efficient, flexible, and fault-tolerant transportation process should be developed. Minimization of transportation cost and timely deliveries in the unpredictable environment are a few of the important issues in logistics. This study suggests a way of transporting goods to destinations at the minimal cost and with the minimal delay by optimally allocating transporting resources. Various attributes in transportation such as due date, priority etc. are also considered. Appropriate transporting resources for each work item is selected by calculating the weighted sum of the cost factor and the delay factor assuming that initial sequences of work items are given. A policy to reallocate transporting resources is also suggested when work items or transporting resources are added or deleted because of accidents or disturbances. This policy provides adaptability to the allocation methodology which enables the system to cope with changing environment by controlling various attributes in transportation. Genetic algorithm is used for this approach.