• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.12 no.1
• /
• pp.78-84
• /
• 1998

The fluid system such as, the quantity control of raw water, chemicals control in the purification, the waste water system as well as in the feed water or circulation system of the power plant and the ventilation system is controlled with the valve and moter pump. The system's performance and the energy saving of the fluid systems depend on control of method and delicacy. Until, PI controller use in these system but it cannot control delicately because of the coupling in the system loop. In this paper we configure a single flow system to the multi variable system and suggest the application of 2-DOF PID controller and the tuning methods by the neural network to the electrical power of the flow control system. the 2-DOF controller follows to a setpoint has a robustness against the disturbance in the results of simulation. Keywords Title, Intelligent control, Neuro control, Flow control, 2 - DOF control., 2 - DOF control.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.690-693
• /
• 2005

In this paper, probabilistic distribution of fatigue life of chassis component is determined statistically by applying the design of experiments and the Pearson system. To construct $p-\varepsilon-N$ curve, the case that fatigue data are random variables is attempted. Probabilistic density function(p.d.f) for fatigue life is obtained by design of experiment and using this p.d.f fatigue reliability about any aimed fatigue life can be calculated. Lower control arm and rear torsion bar of chassis component are selected as examples for analysis. Component load histories, which are obtained by multi-body dynamic simulation for Belsian load history, are used. Finite element analysis are performed using commercial software MSC Nastran and fatigue analysis are performed using FE Fatigue. When strain-life curve itself is random variable, probability density function of fatigue life has very little difference from log-normal distribution. And the case of fatigue data are random variables, probability density functions are approximated to Beta distribution. Each p.d.f is verified by Monte-Carlo simulation.

• ETRI Journal
• /
• v.26 no.4
• /
• pp.321-331
• /
• 2004

In this paper, we propose a new dynamic bandwidth allocation (DBA) algorithm for multimedia services over Ethernet PONs (passive optical networks). The proposed algorithm is composed of a low-level scheduler in the optical network unit (ONU) and a high-level scheduler in the optical line terminal (OLT). The hierarchical DBA algorithm can provide expansibility and efficient resource allocation in an Ethernet PON system in which the packet scheduler is separated from the queues. In the proposed DBA algorithm, the OLT allocates bandwidth to the ONUs in proportion to the weight associated with their class and queue length, while the ONU preferentially allocates its bandwidth to queues with a static priority order. The proposed algorithm provides an efficient resource utilization by reducing the unused remaining bandwidth caused by the variable length of the packets. We also define the service classes and present control message formats conforming to the multi-point control protocol (MPCP) over an Ethernet PON. In order to evaluate the performance, we designed an Ethernet PON system on the basis of IEEE 802.3ah "Ethernet in the first mile" (EFM) using OPNET and carried out simulations. The results are analyzed in terms of the channel utilization, queuing delay, and ratio of the unused remaining bandwidth.

• Journal of the Korean Society for Precision Engineering
• /
• v.24 no.2 s.191
• /
• pp.110-117
• /
• 2007

In this paper, probabilistic distribution of chassis component fatigue life is determined statistically by applying the design of experiments and the Pearson system. To construct p - ${\varepsilon}$ - N curve, the case that fatigue data are random variables is attempted. Probabilistic density function (p.d.f) for fatigue life is obtained by the design of experiment and using this p.d.f fatigue reliability, any aimed fatigue life can be calculated. Lower control arm and rear torsion bar of chassis components are selected as examples for analysis. Component load histories which are obtained by multi-body dynamic simulation for Belsian load history are used. Finite element analysis is performed by using commercial software MSC Nastran and fatigue analysis is performed by using FE Fatigue. When strain-life curve itself is random variable, the probability density function of fatigue life has very little difference from log-normal distribution. And the cases of fatigue data are random variables, probability density functions are approximated to Beta distribution. Each p.d.f is verified by Monte-Carlo simulation.

• Wind and Structures
• /
• v.18 no.3
• /
• pp.235-252
• /
• 2014

An effective numerical technique to calculate the reactions of a multi-spanned transmission line conductor system, under arbitrary loads varying along the spans, is developed. Such variable loads are generated by High Intensity Wind (HIW) events in the form of tornadoes and downburst. First, a semi-closed form solution is derived to obtain the displacements and the reactions at the ends of each conductor span. The solution accounts for the nonlinearity of the system and the flexibility of the insulators. Second, a numerical scheme to solve the derived closed-form solution is proposed. Two conductor systems are analyzed under loads resulting from HIW events for validation of the proposed technique. Non-linear Finite Element Analyses (FEA) are also conducted for the same two systems. The responses resulting from the technique are shown to be in a very good agreement with those resulting from the FEA, which confirms the technique accuracy. Meanwhile, the semi-closed form technique shows superior efficiency in terms of the required computational time. The saving in computational time has a great advantage in predicting the response of the conductors under HIW events, since this requires a large number of analyses to cover different potential locations and sizes of those localized events.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.52 no.7
• /
• pp.424-433
• /
• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• International Journal of Fluid Machinery and Systems
• /
• v.3 no.4
• /
• pp.352-359
• /
• 2010

In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.05a
• /
• pp.404-407
• /
• 2009

The field oriented control of induction motors is widely used in high performance applications. However, detuning caused by parameter disturbance still limits the performance of these drives. In order to accomplish variable speed operation conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation even under ideal field oriented conditions. This paper is proposed adaptive fuzzy controller(AFC) and artificial neural network(ANN) based on the vector controlled induction motor drive system. Also, this paper is proposed control of speed and current using fuzzy adaptation mechanism(FAM), AFC and estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FAM, AFC and ANN controller. Also, this paper is proposed the analysis results to verify the effectiveness of this controller.

• The Transactions of the Korean Institute of Electrical Engineers C
• /
• v.52 no.7
• /
• pp.424-424
• /
• 2003

Evolutionary design related to the optimal design of Polynomial Neural Networks (PNNs) structure for model identification of complex and nonlinear system is studied in this paper. The PNN structure is consisted of layers and nodes like conventional neural networks but is not fixed and can be changable according to the system environments. three types of polynomials such as linear, quadratic, and modified quadratic is used in each node that is connected with various kinds of multi-variable inputs. Inputs and order of polynomials in each node are very important element for the performance of model. In most cases these factors are decided by the background information and trial and error of designer. For the high reliability and good performance of the PNN, the factors must be decided according to a logical and systematic way. In the paper evolutionary algorithm is applied to choose the optimal input variables and order. Evolutionary (genetic) algorithm is a random search optimization technique. The evolved PNN with optimally chosen input variables and order is not fixed in advance but becomes fully optimized automatically during the identification process. Gas furnace and pH neutralization processes are used in conventional PNN version are modeled. It shows that the designed PNN architecture with evolutionary structure optimization can produce the model with higher accuracy than previous PNN and other works.

• Korean Journal of Remote Sensing
• /
• v.19 no.1
• /
• pp.43-52
• /
• 2003

EOC (Electro-Optical Camera) of KOMPSAT-1 (Korea Multi-Purpose SATellite) has been producing land imageries of the world since January 2000. After image data are acquired by EOC, they are transmitted from satellite to ground via X-band RF signal. Then, EOC image data are retrieved and pass through radiometric and geometric corrections to generate standard products of EOC images. After radiometric correction on EOC image data, Modulation Transfer Function (MTF) compensation is applicable on EOC images with user's request for better image quality. MTF compensation is concerned with filtering EOC images to minimize the effect of degradations. For Image Receiving and Processing System (IRPE) at KOMPSAT Ground Station (KGS), Wiener filter is used for MTF compensation of EOC images. If the Pointing Spread Function (PSF) of EOC system is known, signal-to-noise (SNR) power spectra ratio is the only variable which determines the shape of Wiener filter In this paper, MTF compensation in IRPE at KGS is briefly addressed, and MTF compensated EOC images are generated using Wiener filters with various SNR power spectra ratios. MTF compensated EOC images are compared with original EOC 1R images to observe correlations between them. As a result, the effect of SNR power spectra ratio on MTF compensated EOC images is shown.