• 제목/요약/키워드: PSO (Particle Swarm Optimization)

검색결과 500건 처리시간 0.045초

Optimal Switching Pattern for PWM AC-AC Converters Using Bee Colony Optimization

  • Khamsen, Wanchai;Aurasopon, Apinan;Boonchuay, Chanwit
    • Journal of Power Electronics
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    • 제14권2호
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    • pp.362-368
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    • 2014
  • This paper proposes a harmonic reduction approach for a pulse width modulation (PWM) AC-AC converters using Bee Colony Optimization (BCO). The optimal switching angles are provided by BCO to minimize harmonic distortions. The sequences of the PWM switching angles are considered as a technical constraint. In this paper, simulation results from various optimization techniques including BCO, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO) are compared. The test results indicate that BCO can provide a better solution than the others in terms of power quality and power factor improvement. Lastly, experiments on a 200W AC-AC converter confirm the performance of the proposed switching pattern in reducing harmonic distortions of the output waveform.

Design Optimization of an Enhanced Stop-band UWB Bow-Tie Antenna

  • Choi, Kyung;Kim, Hyeong-Seok;Hwang, Hee-Yong
    • 전기전자학회논문지
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    • 제22권3호
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    • pp.793-799
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    • 2018
  • An improved design of Ultra Wide Band(UWB) Bow-Tie antenna, which can control an enhanced wide stop-band, is presented. The mutually coupled slot-pair improves and controls the rejection band. The UWB antenna is composed of an electromagnetically coupled Bow-Tie patch and a parasitic ground patch, whose working frequency is extended to full UWB range in this work. By adding slot-pairs on the main patch and optimizing, they can give any requested wide rejection bands and sharp skirt characteristics, as is often required for UWB antennas and multi-band antennas. All the parameters are precisely calculated by an adequate optimization method. The Particle Swarm Optimization(PSO) technique is appropriately adopted. The proposed design and method is proved to give and control the sharp-skirt wide stop-band to UWB Bow-Tie antennas.

Design of optimal PID controller for the reverse osmosis using teacher-learner-based-optimization

  • Rathore, Natwar S.;Singh, V.P.
    • Membrane and Water Treatment
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    • 제9권2호
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    • pp.129-136
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    • 2018
  • In this contribution, the control of multivariable reverse osmosis (RO) desalination plant using proportional-integral-derivative (PID) controllers is presented. First, feed-forward compensators are designed using simplified decoupling method and then the PID controllers are tuned for flux (flow-rate) and conductivity (salinity). The tuning of PID controllers is accomplished by minimization of the integral of squared error (ISE). The ISEs are minimized using a recently proposed algorithm named as teacher-learner-based-optimization (TLBO). TLBO algorithm is used due to being simple and being free from algorithm-specific parameters. A comparative analysis is carried out to prove the supremacy of TLBO algorithm over other state-of-art algorithms like particle swarm optimization (PSO), artificial bee colony (ABC) and differential evolution (DE). The simulation results and comparisons show that the purposed method performs better in terms of performance and can successfully be applied for tuning of PID controllers for RO desalination plants.

Dynamic modeling and control of IPMC hydrodynamic propulsor

  • Agrahari, Shivendra K.;Mukherjee, Sujoy
    • Smart Structures and Systems
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    • 제20권4호
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    • pp.499-508
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    • 2017
  • The ionic polymer-metal composite (IPMC) is an electroactive polymer material and has a promising potential as actuators for propulsion and locomotion in underwater systems. In this paper a physics based model is used to analyse the actuation dynamics of the IPMC propulsor. Moreover, proportional-integral (PI) controller is used for position control of the tip displacement of IPMC propulsor. PI parameter tuning is performed using particle swarm optimization (PSO) algorithm. Several performance indices have been used as an objective function to optimize the error of the system. Finally, the best tuning method is found out by comparing the results under various performance indices.

최적화된 관측 신뢰도와 변형된 HMM 디코더를 이용한 잡음에 강인한 화자식별 시스템 (A Robust Speaker Identification Using Optimized Confidence and Modified HMM Decoder)

  • ;김진영;나승유
    • 대한음성학회지:말소리
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    • 제64호
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    • pp.121-135
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    • 2007
  • Speech signal is distorted by channel characteristics or additive noise and then the performances of speaker or speech recognition are severely degraded. To cope with the noise problem, we propose a modified HMM decoder algorithm using SNR-based observation confidence, which was successfully applied for GMM in speaker identification task. The modification is done by weighting observation probabilities with reliability values obtained from SNR. Also, we apply PSO (particle swarm optimization) method to the confidence function for maximizing the speaker identification performance. To evaluate our proposed method, we used the ETRI database for speaker recognition. The experimental results showed that the performance was definitely enhanced with the modified HMM decoder algorithm.

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PSO 알고리즘을 이용한 동적부하모델링 (Dynamic Load Modeling Using a PSO algorithm)

  • 김영곤;송화창;이병준
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.93_94
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    • 2009
  • Load modeling has a significant impact on power system analysis and control. Estimating model parameters can be considered as important as stability analysis itself for accurate analysis and control. This paper presents a method for estimating parameters for load models, which include static and dynamic parts, based on particle swarm optimization. The method effectively searches a suitable set of parameters minimizing the fitness function. This paper applies the method to simulation data obtained from 8-bus test system including induction motors.

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IG와 PSO기반 퍼지추론 시스템의 최적 설계 (Optimal Design of Fuzzy Inference System Based on Information Granulation and Particle Swarm Optimization)

  • 김욱동;이동진;오성권
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2009년도 제40회 하계학술대회
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    • pp.1865_1866
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    • 2009
  • 본 연구에서는 복잡하고 비선형 시스템의 모델을 동정하기 위해 Information Granulation에 기반한 퍼지추론 시스템의 새로운 범주를 소개한다. Information Granulation은 근접성, 유사성 EH는 기능성 등에 인하여 서로 결합되는 대상(특히, 데이터)의 연결된 모임으로 간주된다. HCM클러스터링에 의한 Information Granulation은 퍼지 규칙의 전반부 및 후반부에서 사용되는 멤버쉽 함수의 초기 정점과 다항식함수의 초기 값과 같은 퍼지 모델의 초기 파라미터를 결정하는데 도움을 준다. 그리고 초기 파라미터는 PSO 알고리즘과 최소자승법에 의해 효과적으로 동조된다. 제안된 모델은 Box와 jenkins가 사용한 가스로 공정[6]을 모델링하여 기존 퍼지 모델링 방법과 비교 평가한다.

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Particle Swarm Optimization 기법을 이용한 최적조류계산 알고리즘 (Optimal Power Flow by PSO)

  • 김종율;김형수;문경준;이화석;박준호
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
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    • pp.294-296
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    • 2006
  • 최적조류계산은 전력계통에서 여러가지 제약 조건을 만족하면서 경제적으로 계통을 운영하기 일한 기법이다. 종래의 최적조류계산 방법은 주로 선형계획법, 비선형계획법 같은 수치해석적인 방법을 사용하였다. 그러나, 이러한 방법들은 전역 최적해를 구하기 위해서는 목적함수가 convex해야 한다. 또한 계통 규모가 클 경우, 최적해 수렴이 안되거나 수렴이 되더라도 시간이 많이 걸리는 단점이 있다. 최근에는 이러한 문제를 극복하고자 여러 가지 진화연산기법들이 최적조류계산 문제에 적용되고 있다. 본 논문에서는 최근에 등장한 PSO알고리즘을 이용한 최적조류계산 기법을 소개하고 테스트 계통을 대 상으로 그 적용가능성을 검증하였다.

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PSO 알고리즘을 이용한 온실가스배출량에 따른 구역전기사업자의 최적 운영에 관한 연구 (An Optimal Operation of Community Energy System Considering Greenhouse Gas Emission Using PSO Algorithm)

  • 김성열;배인수;김진오
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.498-499
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    • 2008
  • 신재생에너지의 개발, 정부의 규제 완화와 환경적 이유로 인해 배전계통에서 분산전원은 점차 증가하는 추세이다. 최근 분산전원을 소유한 구역전기사업자가 전력시장의 새로운 시장 참여자로서 대두되고 있다. 분산전원을 소유한 구역전기사업자는 최대 이윤을 얻기 위해서 매 시간마다 발전량을 변화시켜야 한다. 본 논문에서는 배전계통에 연계된 분산전원의 최적 운영에 대해서 소개할 것이다. 이 때, 최적화의 목적은 구역전기사업자 이윤의 최대화이며, 국제적 환경규제에 따른 온실가스배출량을 고려하여 발전비용을 산출한다. 산출기법으로 Particle Swarm Optimization 알고리즘을 이용한다.

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Evolutionary Algorithm-based Space Diversity for Imperfect Channel Estimation

  • Ghadiri, Zienab Pouladmast;El-Saleh, Ayman A.;Vetharatnam, Gobi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권5호
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    • pp.1588-1603
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    • 2014
  • In space diversity combining, conventional methods such as maximal ratio combining (MRC), equal gain combining (EGC) and selection combining (SC) are commonly used to improve the output signal-to-noise ratio (SNR) provided that the channel is perfectly estimated at the receiver. However, in practice, channel estimation is often imperfect and this indeed deteriorates the system performance. In this paper, diversity combining techniques based on two evolutionary algorithms, namely genetic algorithm (GA) and particle swarm optimization (PSO) are proposed and compared. Numerical results indicate that the proposed methods outperform the conventional MRC, EGC and SC methods when the channel estimation is imperfect while it shows similar performance as that of MRC when the channel is perfectly estimated.