• 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.

• Journal of international Conference on Electrical Machines and Systems
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• 제3권2호
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• pp.184-189
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• 2014

In this paper, a new design method of vibration suppression controller for multi-inertia (especially, 3-ineritia) resonance systems is proposed. The controller consists of a digital fuzzy controller for speed loop and a digital PI controller for current minor loop. The three scaling factor of the fuzzy controller and two PI controller gains are determined by Differential Evolution (DE). The DE is one of optimization techniques and a kind of evolutionary computation technique. In this paper, we have applied the DE/rand/1/bin strategy to design the optimal controller parameters. Comparing with the conventional design algorithm, the proposed method is able to shorten the time of the controller design to a large extent and to obtain accurate results. Finally, we confirmed the effectiveness of the proposal method by the computer simulations.

• International Journal of Aerospace System Engineering
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• 제7권2호
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• pp.6-12
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• 2020

The precise prediction of future position of satellite depends on the accurate determination of orbit, which is also helpful in performing orbit maneuvers and trajectory correction maneuvers. For estimating the orbit of satellite many methods are being used. Some of the conventional methods are based on (i) Differential Correction (DC) (ii) Extended Kalman Filter (EKF). In this paper, Differential Evolution (DE) is used to determine the orbit. Orbit Determination using DC and EKF requires some initial guess of the state vector to initiate the algorithm, whereas DE does not require an initial guess since a wide range of bounds for the design unknown variables (orbital elements) is sufficient. This technique is uniformly valid for all orbits viz. circular, elliptic or hyperbolic. Simulated observations have been used to demonstrate the performance of the method. The observations are generated by including random noise. The simulation model that generates the observations includes the perturbation due to non-spherical earth up to second zonal harmonic term.

• 인터넷정보학회논문지
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• 제22권1호
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• pp.1-11
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• 2021

Estimation of distribution algorithm (EDA) is a popular stochastic metaheuristic algorithm. EDA has been widely utilized in various optimization problems. However, it has been shown that the diversity of the population gradually decreases during the iterations, which makes EDA easily lead to premature convergence. This article introduces a hybrid estimation of distribution algorithm (EDA) with differential evolution (DE) based on self-adaptive strategy, namely HEDADE-SA. Firstly, an alternative probability model is used in sampling to improve population diversity. Secondly, the proposed algorithm is combined with DE, and a self-adaptive strategy is adopted to improve the convergence speed of the algorithm. Finally, twenty-five benchmark problems are conducted to verify the performance of HEDADE-SA. Experimental results indicate that HEDADE-SA is a feasible and effective algorithm.

• Journal of Electrical Engineering and Technology
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• 제8권1호
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• pp.53-63
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• 2013

To guide the decision making of the expert engineer specialized in power system operation and control; the practical OPF solution should take in consideration the critical situation due to severe loading conditions and fault in power system. Differential Evolution (DE) is one of the best Evolutionary Algorithms (EA) to solve real valued optimization problems. This paper presents simple Differential Evolution (DE) Optimization algorithm to solving multi objective optimal power flow (OPF) in the power system with shunt FACTS devices considering voltage deviation, power losses, and power flow branch. The proposed approach is examined and tested on the standard IEEE-30Bus power system test with different objective functions at critical situations. In addition, the non smooth cost function due to the effect of valve point has been considered within the second practical network test (13 generating units). The simulation results are compared with those by the other recent techniques. From the different case studies, it is observed that the results demonstrate the potential of the proposed approach and show clearly its effectiveness to solve practical OPF under contingent operation states.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권11호
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• pp.5574-5591
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• 2017

Inspired by the idea of Artificial Immune System, many researches of wireless sensor network (WSN) intrusion detection is based on the artificial intelligent system (AIS). However, a large number of generated detectors, black hole, overlap problem of NSA have impeded further used in WSN. In order to improve the anomaly detection performance for WSN, detector generation mechanism need to be improved. Therefore, in this paper, a Differential Evolution Constraint Multi-objective Optimization Problem based Negative Selection Algorithm (DE-CMOP based NSA) is proposed to optimize the distribution and effectiveness of the detector. By combining the constraint handling and multi-objective optimization technique, the algorithm is able to generate the detector set with maximized coverage of non-self space and minimized overlap among detectors. By employing differential evolution, the algorithm can reduce the black hole effectively. The experiment results show that our proposed scheme provides improved NSA algorithm in-terms, the detectors generated by the DE-CMOP based NSA more uniform with less overlap and minimum black hole, thus effectively improves the intrusion detection performance. At the same time, the new algorithm reduces the number of detectors which reduces the complexity of detection phase. Thus, this makes it suitable for intrusion detection in WSN.

• 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.

• Industrial Engineering and Management Systems
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• 제11권3호
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• pp.215-223
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• 2012

This paper focuses on three very similar evolutionary algorithms: genetic algorithm (GA), particle swarm optimization (PSO), and differential evolution (DE). While GA is more suitable for discrete optimization, PSO and DE are more natural for continuous optimization. The paper first gives a brief introduction to the three EA techniques to highlight the common computational procedures. The general observations on the similarities and differences among the three algorithms based on computational steps are discussed, contrasting the basic performances of algorithms. Summary of relevant literatures is given on job shop, flexible job shop, vehicle routing, location-allocation, and multimode resource constrained project scheduling problems.

• 스마트미디어저널
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• 제13권2호
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• pp.129-135
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• 2024

이 연구에서는 MAP-Elites 알고리즘의 연속 최적화 성능을 향상한 새로운 접근법을 제안한다. 기존의 자기 참조 MAP-Elites 알고리즘은 차분 진화 알고리즘의 "DE/rand/1/bin" 연산자를 사용했는데, 이 연산자는 회전 불변이 아니라서 각 변수 간의 상관관계가 높은 경우 성능이 감소하는 문제가 존재한다. 제안하는 알고리즘은 "DE/rand/1/bin" 연산자 대신에 "DE/current-to-rand/1" 연산자를 사용한다. 이 연산자는 회전 불변성을 가지므로 각 변수 간의 상관관계가 높은 분리 불가능 최적화 문제에서도 강건한 성능을 보장할 수 있다. 실험 결과, 제안하는 알고리즘이 비교 알고리즘들에 비해 높은 성능을 발휘함을 확인했다.

• Journal of Applied and Pure Mathematics
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• 제5권3_4호
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• pp.129-164
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• 2023

The aim of this work is to present some interesting results on weighted ergodic functions and prove the existence and uniqueness of Stepanov-like pseudo almost automorphic solutions using the spectral decomposition of the phase space developed by Adimy and co-authors. We also give the next challenge of this work.