• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1530-1533
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• 2005

In this paper, we design a Linear Quadratic Gaussian controller for the active suspension. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Because any definite rules for selecting weights do not exist, we use an optimization-algorithm, Evolution Strategy (ES) to find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies. For the full-state feedback control, Kalman filter observes the full states and Fourier transform is used to detect the frequency of the road.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.11
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• pp.541-546
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• 2006

In a levitation magnet system with large air gap, numerical method is needed because analytic method cannot consider the leakage flux properly. This paper conducted an optimal design of a levitation magnet system with large air gap which was used for an OLED system, where evolution strategy was adopted for optimal design algorithm. Levitation forces near the initial design were calculated first by using finite element method to reduce the computation time. During the optimization process, levitation forces of arbitrary dimension were obtained using the interpolation of the levitation forces which were calculated previously Weight of the maget system was chosen as the object function and it was used minimized.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.06a
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• pp.127-127
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• 2010

This study describes the optimal design of shield to improve the insulation performance of vacuum interrupter(VI). Axi-symmetric finite element routine including floating boundary condition for shields was applied to analyze electric potential and field distribution in VI. A ($\mu-\lambda$) Evolution Strategy(ES) is employed as optimization method. Three design variables of shield are selected for minimizing the maximum electric field strength in VI. Finally, optimal solution for shield is obtained and compared with the result of the prototype.

• ICROS
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• v.1 no.1
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• pp.16-16
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• 1995

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.1
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• pp.16-20
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• 1999

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.9-11
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• 1995

In this paper, tile squirrel case induction motors required multi-objective function are designed. As the objective function of the optimization program, we select the linear combination of loss and mass of motors by using weighting factors. Optimization process is performed by using the evolution strategy (ES). ES is the algorithm that can find the global minimum. To verify validity of the proposed method, a sample design is tried.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1088-1090
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• 1997

This paper presents an effective methodology of optimal environmental and economic operation using evolution strategy. In power systems, evolution strategy, based on natural selection and genetics, can analyze non-linear and discontinuous functions in global search techniques. The formulation using this search techniques is multi-objective function, which consists of fuel cost and environmental effects concerning the pollution of the Earth's atmosphere caused by the emission of $SO_2$ and $NO_x$ from thermal generator plants. The proposed algorithms are applied on system with 6 generator.

• Proceedings of the KIEE Conference
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• 1997.07a
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• pp.21-23
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• 1997

The analysis of the permanent type synchronous motor is performed by using the finite element method (FEM). The optimal design of the permanent magnet is presented for minimizing cogging torque in this paper. The cogging torque is expressed in terms of scalar potential computed by the virtual work formula. The minimization of cogging torque is achieved by using the ( ${\mu}$ + ${\lambda}$ ) Evolution Strategy (ES) and the selected flux densities are used to a constraint.

• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.43-54
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• 2005

For the effective design of automated distribution center composed of Automated Storage/Retrieval System, Automated Guided Vehicle System, and Conveyor System, we proposed an analysis method to determining. design and control parameters with multiple performance objectives using Compromise Programming, which can resolve the dilemma of conflicting objectives. The Evolution Strategy generates the optimal solutions for each objectives. The Analytic Hierarchy Process selects the best solution among the alternatives generated from Evolution Strategy. The Regression Analysis formulates the objective functions for each objectives. By reducing deviations between goal values and target values generated from Analytic Hierarchy Process, Compromise Programming determines design and control parameters by compromising the multiple objectives formulated using Regression Analysis. When the parameters of system are changed, this proposed analysis method has a benefit of reducing costs and time without repeating whole simulation run.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.2B no.4
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• pp.156-161
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• 2002

This paper proposes an optimized universal motor for improving its performance using the finite element method (FEM) with the (1＋1) Evolution Strategy (ES) algorithm. To do this, various design parameters are modified, such as air gap length, shape of motor slot, pole shoe, pole width, and rotor shaft diameter. Two parameters (arc length of stator pole and thickness of pole shoe) are chosen and optimized using the program, and the optimized model is built and tested with a performance measuring system. The measured values of the model are compared with those of the initial and the optimized model to prove the algorithm. As a result, the final model improves its performance compared with those of the initial model.