• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.214-217
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• 2002

The chromosomes of Genetic Algorithm(GA) are classified to be good or not to be by Support vector machines(SVM), and then the only good chromosomes are adopted to the evolution process. By this way, computational load becomes low, so the evolution speed of Genetic Algorithm modified by SVM can be much accelerated than the conventional GA.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.332-343
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• 2022

To address the problems of the gravitational search algorithm (GSA) in which the population is prone to converge prematurely and fall into the local solution when solving the single-objective optimization problem, a sine map jumping gravity search algorithm based on asynchronous learning is proposed. First, a learning mechanism is introduced into the GSA. The agents keep learning from the excellent agents of the population while they are evolving, thus maintaining the memory and sharing of evolution information, addressing the algorithm's shortcoming in evolution that particle information depends on the current position information only, improving the diversity of the population, and avoiding premature convergence. Second, the sine function is used to map the change of the particle velocity into the position probability to improve the convergence accuracy. Third, the Levy flight strategy is introduced to prevent particles from falling into the local optimization. Finally, the proposed algorithm and other intelligent algorithms are simulated on 18 benchmark functions. The simulation results show that the proposed algorithm achieved improved the better performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.27-37
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• 2005

The rectilinear Steiner tree problem (RSTP) is to find a minimum-length rectilinear interconnection of a set of terminals in the plane. It is well known that the solution to this problem will be the minimal spanning tree (MST) on some set Steiner points. The RSTP is known to be NP-complete. The RSTP has received a lot of attention in the literature and heuristic and optimal algorithms have been proposed, A key performance measure of the algorithm for the RSTP is the reduction rate that is achieved by the difference between the objective value of the RSTP and that of the MST without Steiner points. A hybrid evolution strategy on RSTP based upon the Prim algorithm was presented. The computational results show that the evolution strategy is better than the previously proposed other heuristic. The average reduction rate of solutions from the evolution strategy is about 11%, which is almost similar to that of optimal solutions.

• The Transactions of the Korean Institute of Power Electronics
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• v.7 no.4
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• pp.384-394
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• 2002

In this paper, a new control strategy is proposed to improve the quality of the welding products. The conventional nonlinear power control system of spot welders is linearized using nonlinear feedback linearization technique based on differential geometry theory. An evolution strategy(ES) geometry is used to find optimal gain of PI controllers. It tries to find out the optimal control parameters by imitating the natural evolution. Some Simulation and experimental results show that the proposed variable power control system using ES algorithm has better dynamic performances than the conventional one.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.402-409
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• 1999

Variable structure control law is well known to be a robust control algorithm and evolution strategy is used as an effective search algorithm in optimization problems. In this paper, we propose a variable structure controller with time-varying switching surface. We calculate the maximum value of seitching surface gradient that is of the 3rd order polynomial form. Evolution strategy is used to optimize the parameters of the switching surface gradient. Finally, the proposed method is applied to position tracking control for BLDC motor. Experimental results show that the proposed method is more useful than the conventional variable structure controller.

• Smart Structures and Systems
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• v.26 no.3
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• pp.345-360
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• 2020

Modern swarm intelligence heuristic search methods are widely applied in the field of structural health monitoring due to their advantages of excellent global search capacity, loose requirement of initial guess and ease of computational implementation etc. To this end, a hybrid strategy is proposed based on butterfly optimization algorithm (BOA) and differential evolution (DE) with purpose of effective combination of their merits. In the proposed identification strategy, two improvements including mutation and crossover operations of DE, and dynamic adaptive operators are introduced into original BOA to reduce the risk to be trapped in local optimum and increase global search capability. The performance of the proposed algorithm, hybrid butterfly optimization and differential evolution algorithm (HBODEA) is evaluated by two numerical examples of a simply supported beam and a 37-bar truss structure, as well as an experimental test of 8-story shear-type steel frame structure in the laboratory. Compared with BOA and DE, the numerical and experimental results show that the proposed HBODEA is more robust to detect the reduction of stiffness with limited sensors and contaminated measurements. In addition, the effect of search space, two dynamic operators, population size on identification accuracy and efficiency of the proposed identification strategy are further investigated.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.632-637
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• 2008

In real system application, the propeller shaft rate (PSR) estimation algorithm for the feature extraction of the sonar target operates with the following problems: it requires both accurate and efficient the fundamental finding method because it is essential and difficult to distinguish harmonic family composed of the fundamental and its harmonics from the multiple spectral lines in the frequency spectrum-based sonar target classification, and further, it requires an easy design procedure in terms of its structures and parameters. To solve these problems, an evolutionary PSR estimation algorithm using an expert knowledge and the evolution strategy, is proposed. To verify the performance of the proposed algorithm, a sonar target PSR estimation is performed. Simulation results show that the proposed algorithm effectively solves the problems in the realtime system application.

• Journal of Power Electronics
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• v.18 no.1
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• pp.92-102
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• 2018

A sliding mode control (SMC) for servo motors based on the differential evolution (DE) algorithm, called DE-SMC, is proposed in this study. The parameters of SMC should be designed exactly to improve the robustness, realize the precision positioning, and reduce the steady-state speed error of the servo drive. The main parameters of SMC are optimized using the DE algorithm according to the speed feedback information of the servo motor. The most significant influence factor of the DE algorithm is optimization iteration. A suitable iteration can be achieved by the tested optimization process profile of the main parameters of SMC. Once the parameters of SMC are optimized under a convergent iteration, the system realizes the given performance indices within the shortest time. The experiment indicates that the robustness of the system is improved, and the dynamic and steady performance achieves the given performance indices under a convergent iteration when motor parameters mismatch and load disturbance is added. Moreover, the suitable iteration effectively mitigates the low-speed crawling phenomenon in the system. The correctness and effectiveness of DE-SMC are verified through the experiment.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.2
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• pp.279-285
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• 2016

In this paper, a cogging torque of IPM(Interior Permanent Magnet)-type BLDC motor is analyzed by FE program and the optimized notch on the rotor surface is designed to minimize the torque ripple. A differential evolution strategy algorithm and a response surface method are employed to optimize the rotor notch. In order to verify the proposed algorithm, an IPM BLDC motor is used, which is 50 kW, 8 poles, 48 slots and 1200 rpm at the rated speed. Its characteristics of the motor is calculated by FE program and 4 design variables are set on the rotor notch. The initial shape of the notch is like a non-symmetric half-elliptic and it is optimized by the developed algorithm. The cogging torque of the final model is reduced to $1.5[N{\cdot}m]$ from $5.2[N{\cdot}m]$ of the initial, which is about 71 % reduction. Consequently, the proposed algorithm for the cogging torque reduction of IPM-type BLDC motor using the rotor notch design seems to be very useful to a mechanical design for reducing noise and vibration.

• Proceedings of the KSME Conference
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• 2005.11a
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• pp.214.1-214.1
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• 2005