• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.83-90
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• 2011

The evaluation of Conflict detection and Resolution Algorithms require the use of analytical that describe encounter flight safety and the costs and benefits of optimization maneuver. A number of such algorithms have been applied in the past to the free flight. Each algorithm has benefits and limitations, and flight safety may be facilitated by combining the best features of various techniques. This paper studied a summary of conflict detection and resolution algorithm approaches. Algorithm techniques are categorized and the fundamental assumptions, capabilities, and limitations of each approach are described. The Algorithms are evaluated and compared based on their applicability to free flight airspace conflict situations.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1069-1074
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• 1989

A discrete-time learning control for robotic manipulators is studied using its pulse transfer function. Firstly, discrete-time learning stability condition which is applicable to single-input two-outputs systems is derived. Secondly, stability of learning algorithm with position signal is studied. In this case, when sampling period is small, the algorithm is not stable because of an unstable zero of the system. Thirdly, stability of algorithm with position and velocity signals is studied. In this case, we can stabilize the learning control system which is unstable in learning with only position signal. Finally, simulation results on the trajectory control of robotic manipulators using the discrete-time learning control are shown. This simulation results agree well with the analytical ones.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.6 s.249
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• pp.698-704
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• 2006

This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2003.04a
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• pp.177-184
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• 2003

The purposes of this study are to develop the real coding genetic algorithm and to obtain the shape optimization of a cable domes by using this scheme. Generally, the structural performance of the cable dome is influenced very sensitively by prestress, geometry and length of the mast because of flexible structures. So, it is very important to decide the optimum shape to get maximum stiffness of cable domes. We use the two models to verify the usefulness of this algorithm for shape optimization and analyze the roof system of Seoul olympic gymnastic arena as one analytical model of practical structures

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.64-66
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• 1995

This paper presents a new approach to evaluate optimal basic reliability indices of electric distribution systems using genetic algorithm. The use of optimal reliability evaluation is an important aspect of distribution system planning and operation to determine adequacy reliability level of each area. In this paper, the reliability model is based on the analytical method, connecting component failure to load point outage in each section. The proposed method applies genetic algorithm to calculate the optimal values of basic reliability indices, ie. failure rate and repair time, for a load point in the power distribution system, subject to minimizing interruption cost. Test results for the model system are reported in the paper compared with a direct optimization method(gradient projection).

• Journal of the Optical Society of Korea
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• v.18 no.5
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• pp.442-448
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• 2014

For the first time, a novel analytical model of the net gain for a Raman-EDFA hybrid optical amplifier (HOA) is proposed and its various parameters optimized using a genetic algorithm. Our method has been shown to be robust in the simultaneous analysis of multiple parameters (Raman length, EDFA length, and pump powers) to obtain large gain. The optimized HOA is further investigated at the system level for the scenario of a 50-channel DWDM system with 0.2-nm channel spacing. With an optimized HOA, a flat gain of >17 dB is obtained over the effective ITU-T wavelength grid with a variation of less than 1.5 dB, without using any gain-flattening technique. The obtained noise figure is also the lowest value ever reported for a Raman-EDFA HOA at reduced channel spacing.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.2
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• pp.73-79
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• 1987

This paper describes a new algorithm to evaluate the production cost for a generation system including energy-limited hydroelectric plants. The algorithm is based upon the analytical production costing model developed under the assumption of Gaussian probabilistic distribution of random load fluctuations and plant outages. Hydro operation and pumped storage operation have been dealt with in the previous papers using the concept of peak-shaving operation. In this paper, the hydro problem is solved by using a new version of the gradient projection method that treats the upper / lower bounds of variables saparately and uses a specified initial active constraint set. Accuracy and validity of the algorithm are demonstrated by comparing the result with that of the peak-shaving model.

• Proceedings of the KIPE Conference
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• 2015.07a
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• pp.177-178
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• 2015

This paper presents a neutral point deviation compensating control algorithm applied to a 3-level NPC converter. The neutral point deviation is analyzed with a focus on the current flowing out of or into the neutral point of the dc link. Based on the zero sequence components of the reference voltages, this paper analyzes the neutral point deviation and balancing control for 3-level NPC converter. An analytical method is proposed to calculate the injected zero sequence voltage for NP balancing based on average neutral current. This paper also proposes a control scheme compensating for the neutral point deviation under generalized unbalanced grid operating conditions. The positive and negative sequence components of the pole voltages and ac input currents are employed to accurately explain the behavior of 3-level NPC converter. Simulation and experimental results for a test set up of 30kW are shown to verify the validity of the proposed algorithm.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.807-813
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• 2006

The objective of this study is to develop a rule-based fault detection algorithm and an experimental verification using an artificial air handling unit. To develop an analytical algorithm which precisely detects a tendency of faulty component, energy equations at each control volume of AHU were applied. An experimental verification was conducted on the HVAC simulator. The rule based FDD algorithm isolated a faulted sensor from HVAC components in summer and winter conditions.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.18-27
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• 2007

The conventional normalized least mean square (NLMS) algorithm is the most widely used for adaptive identification within a non-stationary input context. The convergence of the NLMS algorithm is independent of environmental changes. However, its steady state performance is impaired during input sequences with low dynamics. In this paper, we propose a new NLMS algorithm which is, in the steady state, insensitive to the time variations of the input dynamics. The square soot (SR)-NLMS algorithm is based on a normalization of the LMS adaptive filter input by the Euclidean norm of the tap-input. The tap-input power of the SR-NLMS adaptive filter is then equal to one even during sequences with low dynamics. Therefore, the amplification of the observation noise power by the tap-input power is cancelled in the misadjustment time evolution. The harmful effect of the low dynamics input sequences, on the steady state performance of the LMS adaptive filter are then reduced. In addition, the square root normalized input is more stationary than the base input. Therefore, the robustness of LMS adaptive filter with respect to the input non stationarity is enhanced. A performance analysis of the first- and the second-order statistic behavior of the proposed SR-NLMS adaptive filter is carried out. In particular, an analytical expression of the step size ensuring stability and mean convergence is derived. In addition, the results of an experimental study demonstrating the good performance of the SR-NLMS algorithm are given. A comparison of these results with those obtained from a standard NLMS algorithm, is performed. It is shown that, within a non-stationary input context, the SR-NLMS algorithm exhibits better performance than the NLMS algorithm.