• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.8-15
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• 2006

Since the power swing depends on the operating time of the relay, the swing's magnitude can be reduced by an autoreclosure relaying system with an optimal reclosing algorithm. This paper proposes a method for stability improvement using optimal reclosure relaying. An optimal reclosure algorithm is applied to identify both temporary and permanent faults, and to predict system stability by applying WAM and high speed communication technology. It provides optimal control by predicting and determining the degree of stability, considering the real time transient stability using EEEAC. For temporary faults, the algorithm determines the system's stability and either recloses optimally for stable systems, or inserts series capacitance before optimal reclosure for unstable systems. It also applies an optimal reclosure algorithm to minimize shock and damage to the power system when reclosure fails due to permanent faults.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.393-402
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• 2000

Recently 5-axis NC machines are widely used in Korea. Since 5-axis machines have two more degrees of freedom than 3-axis machines, it is very important to find desirable tool positions(locations and orientations) in order to make an efficient use of expensive 5-axis NC machines. In this research an algorithm to determine “optimal” tool positions for 5-axis machining of sculptured surfaces is developed. For given CC(Cutter Contact) points, this algorithm determines the cutter axis vectors which minimize cusp heights and satisfy constraints. To solve the optimal problem, we deal with following major issues: (1) an approximation method of a cusp height as a measure of optimality (2) Identifying some properties of the optimal problem (3) a search method for the optimal points using the properties. By using a polyhedral model as a machining surface, this algorithm applies to sculptured surfaces covering: overhanged surface.

• International Journal of CAD/CAM
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• v.6 no.1
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• pp.193-198
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• 2006

Plunge milling is the fastest way to mill away large volumes of metal in the axial direction. The residual volume (inaccessible volume by the plungers) is minimized when selecting a specific direction of filling. This direction is known as the optimal inclination angle for filling of the plunged area. This paper proposes a new algorithm to calculate the optimal inclination angle of filling and to fill the plunged area with multi-plungers sizes. The proposed algorithm uses the geometry of the 2D area of the shape that being cutting to estimate the optimal inclination angle of filling. It is found that, the optimal inclination angle for filling of the plunged area is the same direction as the longer width of the equivalent convex polygon of the boundary contour. The results of the tested examples show that, the residual volume is minimized when comparing the proposed algorithm with the previous method.

• Journal of Mechanical Science and Technology
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• v.14 no.7
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• pp.764-772
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• 2000

In this paper, an engine-CVT integrated control algorithm is suggested by considering the inertia torque and the CVT ratio change response lag in acceleration. In order to compensate for drive torque time delay due to CVT response lag, two algorithms are presented: (1) an optimal engine torque compensation algorithm, and (2) an optimal engine speed compensation algorithm. Simulation results show that the optimal engine speed compensation algorithm gives better engine operation around the optimal operation point compared to the optimal torque compensation while showing nearly the same acceleration response. The performance of the proposed engine-CVT integrated control algorithms are compared with those of conventional CVT control, and It is found that optimal engine operation can be achieved by using integrated control during acceleration, and improved fuel economy can be expected while also satisfying the driver's demands.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.704-710
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• 2018

For the optimal design of electromagnetic device involving uncertainties in design variables, this paper proposes a new reliability-based optimal design algorithm for multiple constraints problems. Through optimizing the nominal objective function and maximizing the minimum reliability, a set of global optimal reliable solutions representing different reliability levels are obtained by the multi-objective particle swarm optimization algorithm. Applying the sensitivity-assisted Monte Carlo simulation method, the numerical efficiency of optimization procedure is guaranteed. The proposed reliability-based algorithm supplying multi-reliable solutions is investigated through applications to analytic examples and the optimal design of two electromagnetic problems.

• Journal of Communications and Networks
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• v.7 no.1
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• pp.65-75
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• 2005

In this paper, we consider a scenario in which the source has been offered QoS guarantees subject to token-bucket regulation. The rate of the source should be controlled such that it conforms to the token-bucket regulation, and also the distortion obtained is the minimum. We have developed an optimal scheduling algorithm for offline (like pre-recorded video) sources with convex distortion function and which can not tolerate any delay. This optimal offline algorithm has been extended for the real-time online source by predicting the number of packets that the source may send in future. The performance of the online scheduler is not substantially degraded as compared to that of the optimal offline scheduler. A sub-optimal offline algorithm has also been developed to reduce the computational complexity and it is shown to perform very well. We later consider the case where the source can tolerate a fixed amount of delay and derive optimal offline algorithm for such traffic source.

• International Journal of Automotive Technology
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• v.8 no.5
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• pp.563-573
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• 2007

Optimal design of an automotive catalytic converter for minimization of cold-start emissions is numerically performed using a micro genetic algorithm for two optimization problems: optimal geometry design of the monolith for various operating conditions and optimal axial catalyst distribution. The optimal design process considered in this study consists of three modules: analysis, optimization, and control. The analysis module is used to evaluate the objective functions with a one-dimensional single channel model and the Romberg integration method. It obtains new design variables from the control module, produces the CO cumulative emissions and the integral value of a catalyst distribution function over the monolith volume, and provides objective function values to the control module. The optimal design variables for minimizing the objective functions are determined by the optimization module using a micro genetic algorithm. The control module manages the optimal design process that mainly takes place in both the analysis and optimization modules.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.580-583
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• 2003

The general time optimal control law provides the optimal solution for a minimum time control problem. But in most real systems with disturbances and model uncertainties, the time optimal control law leads to chattering effect. This chattering effect can cause the system to be unstable. Therefore, we propose a robust optimal control algorithm for the nonlinear second order systems with model uncertainty. The proposed algorithm is combined with bang-bang control and sliding mode control. Thus the proposed algorithm has two state space regions to implement to control algorithm. In each region, the appropriate linear or nonlinear feedback control law is used satisfying the dynamic system equations. Simulation results show the superiority of the proposed controller in comparison with pure time optimal control(bang-bang control).

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.84-92
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• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• Journal of Korean Society of Steel Construction
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• v.21 no.4
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• pp.361-373
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• 2009

Using the genetic algorithm, the optimal-design technique of the Nielsen arch bridge was proposed in this paper. The design parameters were the arch-rise ratio and the steel weight ratio of the Nielsen arch bridge, and optimal-design techniques were utilized to analyze the behavior of the bridge. The optimal parameter values were determined for the estimated optimal level. The parameter determination requires the standardization of the safety, utility, and economic concepts as the critical factors of a structure. For this, a genetic algorithm was used, whose global-optimal-solution search ability is superior to the optimization technique, and whose object function in the optimal design is the total weight of the structure. The constraints for the optimization were displacement, internal stress, and time and space. The structural analysis was a combination of the small displacement theory and the genetic algorithm, and the runtime was reduced for parallel processing. The optimal-design technique that was developed in this study was employed and deduced using the optimal arch-rise ratio, steel weight ratio, and optimal-design domain. The optimal-design technique was presented so it could be applied in the industry.