• Title/Summary/Keyword: multi-point methods

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A Simple Control Strategy for Balancing the DC-link Voltage of Neutral-Point-Clamped Inverters at low modulation index (Neutral-Point-Clamped 인버터의 저 변조지수에서 DC 링크 전압 균형을 위한 간단한 컨트롤 기법)

  • Ma C.S.;Kim T.J.;Kang D.W.;Hyun D.S.
    • Proceedings of the KIPE Conference
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    • 2003.07b
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    • pp.560-564
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    • 2003
  • This paper proposes a simple control strategy based on the discontinuous PWM(DPWM) to balance the DC-link voltage of three-level Neutral-Point-Clamped(WPC) inverters at low modulation index. New DPWM methods in multi-level inverter are also introduced. The proposed DPWM method changes the path and duration to flow the neutral point current out of or into neutral point of the DC-link and it makes the overall fluctuation of the DC-link voltage zero during a sampling time of reference voltage vector. Therefore, the voltage of the DC-link can be balanced fairly well and also the voltage ripple of the DC-link is reduced significantly. Moreover, comparing with conventional methods, the proposed strategy is very simple. The validity of the proposed DPWM method is verified by experiment

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Integrating Ant Colony Clustering Method to a Multi-Robot System Using Mobile Agents

  • Kambayashi, Yasushi;Ugajin, Masataka;Sato, Osamu;Tsujimura, Yasuhiro;Yamachi, Hidemi;Takimoto, Munehiro;Yamamoto, Hisashi
    • Industrial Engineering and Management Systems
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    • v.8 no.3
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    • pp.181-193
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    • 2009
  • This paper presents a framework for controlling mobile multiple robots connected by communication networks. This framework provides novel methods to control coordinated systems using mobile agents. The combination of the mobile agent and mobile multiple robots opens a new horizon of efficient use of mobile robot resources. Instead of physical movement of multiple robots, mobile software agents can migrate from one robot to another so that they can minimize energy consumption in aggregation. The imaginary application is making "carts," such as found in large airports, intelligent. Travelers pick up carts at designated points but leave them arbitrary places. It is a considerable task to re-collect them. It is, therefore, desirable that intelligent carts (intelligent robots) draw themselves together automatically. Simple implementation may be making each cart has a designated assembly point, and when they are free, automatically return to those points. It is easy to implement, but some carts have to travel very long way back to their own assembly point, even though it is located close to some other assembly points. It consumes too much unnecessary energy so that the carts have to have expensive batteries. In order to ameliorate the situation, we employ mobile software agents to locate robots scattered in a field, e.g. an airport, and make them autonomously determine their moving behaviors by using a clustering algorithm based on the Ant Colony Optimization (ACO). ACO is the swarm intelligence-based methods, and a multi-agent system that exploit artificial stigmergy for the solution of combinatorial optimization problems. Preliminary experiments have provided a favorable result. In this paper, we focus on the implementation of the controlling mechanism of the multi-robots using the mobile agents.

Performance Analysis of the AC-DC Transformation Method using Multi-level Pulsating Current and Selection Switch (다단 맥류 스위칭을 이용한 교류-직류 변환의 성능분석)

  • Lee, Jae-Seang
    • Journal of the Korea Institute of Military Science and Technology
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    • v.13 no.4
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    • pp.586-593
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    • 2010
  • In this paper, I have proposed that the 1st and 2nd AC-DC transformation methods using multi-level pulsating currents and selection switches. Through making the rectified voltage of the proposed AC-DC translation which is similar to reference voltage by selecting from multi-level pulsating currents, the proposed translation has dramatically reduced the ripple voltage. I have compared the performance of the DC voltage, the ripple voltage and the peak to peak voltage of the proposed method with the conventional method. The simulation results show that the proposed 2nd method has the better performance than the 1st method in the point of average DC voltage drop and peak to peak voltage increase.

The Automatic Coordination Model for Multi-Agent System Using Learning Method (학습기법을 이용한 멀티 에이전트 시스템 자동 조정 모델)

  • Lee, Mal-Rye;Kim, Sang-Geun
    • The KIPS Transactions:PartB
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    • v.8B no.6
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    • pp.587-594
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    • 2001
  • Multi-agent system fits to the distributed and open internet environments. In a multi-agent system, agents must cooperate with each other through a coordination procedure, when the conflicts between agents arise. Where those are caused by the point that each action acts for a purpose separately without coordination. But previous researches for coordination methods in multi-agent system have a deficiency that they cannot solve correctly the cooperation problem between agents, which have different goals in dynamic environment. In this paper, we suggest the automatic coordination model for multi-agent system using neural network and reinforcement learning in dynamic environment. We have competitive experiment between multi-agents that have complexity environment and diverse activity. And we analysis and evaluate effect of activity of multi-agents. The results show that the proposed method is proper.

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Spatio-temporal Load Forecasting Considering Aggregation Features of Electricity Cells and Uncertainties in Input Variables

  • Zhao, Teng;Zhang, Yan;Chen, Haibo
    • Journal of Electrical Engineering and Technology
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    • v.13 no.1
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    • pp.38-50
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    • 2018
  • Spatio-temporal load forecasting (STLF) is a foundation for building the prediction-based power map, which could be a useful tool for the visualization and tendency assessment of urban energy application. Constructing one point-forecasting model for each electricity cell in the geographic space is possible; however, it is unadvisable and insufficient, considering the aggregation features of electricity cells and uncertainties in input variables. This paper presents a new STLF method, with a data-driven framework consisting of 3 subroutines: multi-level clustering of cells considering their aggregation features, load regression for each category of cells based on SLS-SVRNs (sparse least squares support vector regression networks), and interval forecasting of spatio-temporal load with sampled blind number. Take some area in Pudong, Shanghai as the region of study. Results of multi-level clustering show that electricity cells in the same category are clustered in geographic space to some extent, which reveals the spatial aggregation feature of cells. For cellular load regression, a comparison has been made with 3 other forecasting methods, indicating the higher accuracy of the proposed method in point-forecasting of spatio-temporal load. Furthermore, results of interval load forecasting demonstrate that the proposed prediction-interval construction method can effectively convey the uncertainties in input variables.

A Study on the Improvement of Vehicle Ride Comfort by Genetic Algorithms (유전자 알고리즘을 이용한 차량 승차감 개선에 관한 연구)

  • 백운태;성활경
    • Transactions of the Korean Society of Automotive Engineers
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    • v.6 no.4
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    • pp.76-85
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    • 1998
  • Recently, Genetic Algorithm(GA) is widely adopted into a search procedure for structural optimization, which is a stochastic direct search strategy that mimics the process of genetic evolution. This methods consist of three genetics operations maned selection, crossover and mutation. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA, being zero-order method, is very simple. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher probability of converge to global optimum compared to traditional techniques which take one-point search method. In this study, a method of finding the optimum values of suspension parameters is proposed by using the GA. And vehicle is modelled as planar vehicle having 5 degree-of-freedom. The generalized coordinates are vertical motion of passenger seat, sprung mass and front and rear unsprung mass and rotate(pitch) motion of sprung mass. For rapid converge and precluding local optimum, share function which distribute chromosomes over design bound is introduced. Elitist survival model, remainder stochastic sampling without replacement method, multi-point crossover method are adopted. In the sight of the improvement of ride comfort, good result can be obtained in 5-D.O.F. vehicle model by using GA.

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The Optimization of Sizing and Topology Design for Drilling Machine by Genetic Algorithms (유전자 알고리즘에 의한 드릴싱 머신의 설계 최적화 연구)

  • Baek, Woon-Tae;Seong, Hwal-Gyeong
    • Journal of the Korean Society for Precision Engineering
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    • v.14 no.12
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    • pp.24-29
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    • 1997
  • Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

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Zero-one Integer Programming Approach to Determine the Minimum Break Point Set in Multi-loop and Parallel Networks

  • Moirangthem, Joymala;Dash, Subhransu Sekhar;Ramaswami, Ramas
    • Journal of Electrical Engineering and Technology
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    • v.7 no.2
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    • pp.151-156
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    • 2012
  • The current study presents a zero-one integer programming approach to determine the minimum break point set for the coordination of directional relays. First, the network is reduced if there are any parallel lines or three-end nodes. Second, all the directed loops are enumerated to reduce the iteration. Finally, the problem is formulated as a set-covering problem, and the break point set is determined using the zero-one integer programming technique. Arbitrary starting relay locations and the arbitrary consideration of relay sequence to set and coordinate relays result in navigating the loops many times and futile attempts to achieve system-wide relay coordination. These algorithms are compared with the existing methods, and the results are presented. The problem is formulated as a setcovering problem solved by the zero-one integer programming approach using LINGO 12, an optimization modeling software.

N-point modified exponential model for household projections in Korea using multi-point register-based census data

  • Saebom Jeon;Tae Yeon Kwon
    • Communications for Statistical Applications and Methods
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    • v.31 no.4
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    • pp.377-391
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    • 2024
  • Accurate household projections are essential for sectors such as housing supply and tax policy planning, given the rapid social changes like declining birthrates, an aging population, and a rise in single-person households that impact household size and type. Korea introduced its first register-based census in 2015, transitioning from five-year general survey-based approach to an annual administrative data-based census. This change in census allows for more frequent and effective capturing the rapid demographic shifts and trends. However, this change in census has caused challenges in future projection by the existing household projection model due to the rapid dynamics. This paper proposes a new household projection method, the N-point Modified Exponential Model (MEM), that accurately reflects register-based census data and mitigates the impact of rapid demographic changes, in three types: the Weighted N-point MEM, the Regression-based N-point MEM, and the Rolling Weighted N+point MEM. Using register-based census data from 2016 to 2020 to forecast household headship rates by age, household size, and household type to 2051, the N-point modified exponential model outperformed the existing model in both long- and short-term forecast accuracy, suggesting its suitability as a future household projection model for Korea.

An Analysis of Similarity Measures for Area-based Multi-Image Matching (다중영상 영역기반 영상정합을 위한 유사성 측정방법 분석)

  • Noh, Myoung-Jong;Kim, Jung-Sub;Cho, Woo-Sug
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.2
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    • pp.143-152
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    • 2012
  • It is well-known that image matching is necessary for automatic generation of 3D data such as digital surface data from aerial images. Recently developed aerial digital cameras allow to capture multi-strip images with higher overlaps and less occluded areas than conventional analogue cameras and that much of researches on multi-image matching have been performed, particularly effective methods of measuring a similarity among multi-images using point features as well as linear features. This research aims to investigate similarity measuring methods such as SSD and SNCC incorporated into a area based multi-image matching method based on vertical line locus. In doing this, different similarity measuring entities such as grey value, grey value gradient, and average of grey value and its gradient are implemented and analyzed. Further, both dynamic and pre-fixed adaptive-window size are tested and analyzed in their behaviors in measuring similarity among multi-images. The aerial images used in the experiments were taken by a DMC aerial frame camera in three strips. The over-lap and side-lap are about 80% and 60%, respectively. In the experiment, it was found that the SNCC as similarity measuring method, the average of grey value and its gradient as similarity measuring entity, and dynamic adaptive-window size can be best fit to measuring area-based similarity in area based multi-image matching method based on vertical line locus.