• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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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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• 제18권3호
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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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.

• 전력전자학회논문지
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• 제7권4호
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• pp.384-394
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• 2002

본 논문은 기존의 정전력 제어 대신에 용접품질을 향상시키기 위해 새로운 제어기법을 제안하였다. 제안된 방식을 구현하기 위해 미분기하학 이론을 근거로 한 비선형 피드백 선형화 기법을 이용하여 스폿용접 시스템을 선형시스템으로 한 후 진화전략을 이용하여 PI제어기의 최적 이득을 얻는다. 진화전략은 제어파라미터 최적화 문제를 풀기 위한 방법으로 자연진화의 원리를 모방한 알고리즘이다. 시뮬레이션과 실험결과는 진화전략에 의한 가변전력 제어의 성능이 기존의 제어방법보다 훨씬 더 우수하다는 것을 보여준다.

• 대한전기학회논문지:전력기술부문A
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• 제48권4호
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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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• 제26권3호
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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.

• 한국지능시스템학회논문지
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• 제18권5호
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• pp.632-637
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• 2008

실제 시스템 적용에 있어서, 소나 표적의 특징정보추출을 위한 PSR(Propeller Shaft Rate) 추정 알고리즘은 다음과 같은 문제점들을 가지고 있다. 즉, 주파수 스펙트럼 기반의 소나 표적 식별에 있어서 다중의 스펙트럼 선들로부터 기본 주파수와 그 고조파들로 구성된 하모닉군을 구별하는 깃은 필수적이면서도 어렵기 때문에 정확하고 효율적인 기본주파수 발견법을 요구한다. 나아가, 구조와 파라메터에 있어서 용이한 설계 절차를 요구한다 이 문제들을 해결하기 위해서 전문가 지식 및 진화 전략(ES : Evolution Strategy)을 이용하는 진화적인PSR 추정 알고리즘이 제안되었다. 제안된 알고리즘의 성능을 검증하기 위해서는 소나 표적의 PSR 추정이 수행되었다. 시뮬레이션 결과는 제안된 알고리즘이 실시간 시스템 적용에서 존재하는 문제점들을 효과적으로 해결할 수 있음을 보여준다.

• Journal of Power Electronics
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• 제18권1호
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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.

• 전기학회논문지
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• 제65권2호
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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.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2005년도 창립60주년 기념 추계 학술대회
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• pp.214.1-214.1
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• 2005