• 제목/요약/키워드: intelligent algorithm

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국제해상충돌예방규칙에 따른 군집 무인수상정의 편대 제어 알고리즘 연구 (A Study on the Formation Control Algorithm of Multi-USVs According to COLREGs)

  • 허진영;김현석;심성준;김주영;유재관;권용진
    • 한국군사과학기술학회지
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    • 제25권6호
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    • pp.586-595
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    • 2022
  • In this paper, we propose a formation control algorithm for multi-USVs according to COLREGs. First, we applied the Dynamic Window Approach algorithm that can reflect the kinematic characteristics for the path movement of USVs. Then, we propose a virtual structure-based virtual leader-follower method that applies the advantages of leader-follower and virtual structure methods among conventional formation control algorithms for stability. Next, we proposed a collision avoidance algorithm according to all COLREGs when encountering an opposing ship by adding COLREGs situational conditions to the virtual leader, and finally confirmed the feasibility of the proposed method through simulation.

위치.속도 제어 방식을 이용한 매스터 컨트롤러 지능형 혼합 제어 알고리즘 (An intelligent mixed mode algorithm of a master controller using position and rate mode)

  • 김기홍;권동수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.245-248
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    • 1997
  • The control modes used in teleoperation are position control mode, and rate control mode. This paper presents the problems of the conventional control modes, through simulation, proposes an intelligent mixed control mode that converts the operation mode between the position mode and the rate mode intelligently by judging the operator's intention using the real-time measurement data. The effectiveness of the proposed intelligent mixed control mode is demonstrated and compared to other typical control modes through simulation and actual experiment.

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A Study on Intelligent Decentralized Active Suspension Control System with Descriptor LMI Design Method

  • Park, Jung-Hyen
    • Journal of information and communication convergence engineering
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    • 제6권2호
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    • pp.198-203
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    • 2008
  • An Intelligent optimal control system design algorithm in active suspension equipment adopting linear matrix inequalities control system design theory with representing by descriptor system form is presented. The validity of the linear matrix inequalities intelligent decentralized control system design with representing by descriptor system form in active suspension system through the numerical examples is also investigated.

Optimal Job Scheduling for RGV with multiple buffers

  • Jeong, Chan-Doo;Lee, Su-Jeong;Kim, Jin-Ki;Sung, Hak-Kyung
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.84.3-84
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    • 2001
  • Suggesting the standard of optimal transferring for one RGV or two RGV, which have multiple buffers, using average delivery time and sigma in the straight line working place. For performing the optimal transferring, present RGV-Job Dispatching algorithm, which is possible to apply in realtime, and apply random job occurrence conditions for examining the possibility to apply various real environments.

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영상 데이터를 이용한 순차적인 지능형 영상 분석 DSP 시스템의 연구 (A study on Sequential Intelligent DSP System using Image Data)

  • 장일식;강인구;전지혜;박구만
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2010년도 춘계학술대회 논문집
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    • pp.2064-2068
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    • 2010
  • In this paper, we introduced a sequential intelligent image analysis system(SIIAS). This system is implemented using PTZ camera with intelligent analysis algorithm and TI's Davinci DM6446. Enter, abandon, removal and cross functions are included in our system. These functions can be used individually or in combination for object monitoring and tracking. Sequential intelligent function processing is more efficient than the previous one by virtue of accurate observation, wide area monitoring and low cost.

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Neural Network Modeling of PECVD SiN Films and Its Optimization Using Genetic Algorithms

  • Han, Seung-Soo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제1권1호
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    • pp.87-94
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    • 2001
  • Silicon nitride films grown by plasma-enhanced chemical vapor deposition (PECVD) are useful for a variety of applications, including anti-reflecting coatings in solar cells, passivation layers, dielectric layers in metal/insulator structures, and diffusion masks. PECVD systems are controlled by many operating variables, including RF power, pressure, gas flow rate, reactant composition, and substrate temperature. The wide variety of processing conditions, as well as the complex nature of particle dynamics within a plasma, makes tailoring SiN film properties very challenging, since it is difficult to determine the exact relationship between desired film properties and controllable deposition conditions. In this study, SiN PECVD modeling using optimized neural networks has been investigated. The deposition of SiN was characterized via a central composite experimental design, and data from this experiment was used to train and optimize feed-forward neural networks using the back-propagation algorithm. From these neural process models, the effect of deposition conditions on film properties has been studied. A recipe synthesis (optimization) procedure was then performed using the optimized neural network models to generate the necessary deposition conditions to obtain several novel film qualities including high charge density and long lifetime. This optimization procedure utilized genetic algorithms, hybrid combinations of genetic algorithm and Powells algorithm, and hybrid combinations of genetic algorithm and simplex algorithm. Recipes predicted by these techniques were verified by experiment, and the performance of each optimization method are compared. It was found that the hybrid combinations of genetic algorithm and simplex algorithm generated recipes produced films of superior quality.

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클래스 구분력이 없는 특징 소거법 (Removing non-informative features weakening of class separability)

  • 이재성;김대원
    • 한국지능시스템학회:학술대회논문집
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    • 한국지능시스템학회 2007년도 추계학술대회 학술발표 논문집
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    • pp.59-62
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    • 2007
  • 본 논문에서는 불균형 및 Under-sampling된 바이오 데이터에 대하여 클래스 구분력이 없는 특징의 소거를 통해 이후 이어질 FLDA 둥 다양한 방법론올 적용할 수 있는 방법을 제안하고자 한다. 제안하는 알고리즘은 평균과 분산을 통해 클래스의 형태를 결정하는 기존 방법론의 문제점을 회피할 수 있는 방법을 제공하며, 클래스 구분력에 중점을 두어 특정을 선별하였을 경우 선별된 특정들의 상관 계수가 높은 문제를 극복할 수 있도록 한다. 이에 따라 알고리즘이 선택한 특정집합은 서로의 특징에 대해 상관계수가 낮으며, 클래스의 구분력이 높은 특정을 갖게 된다.

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유전알고리즘을 이용한 철도차량 경제운전 모델 개발 (Development of Economical Run Model for Electric Railway Vehicle using Genetic Algorithm)

  • 이태형;박춘수;최성훈;김석원
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
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    • pp.364-366
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    • 2007
  • 본 논문은 철도차량이 주행하는 선로에 존재하는 수많은 곡선과 경사, 속도 제한 조건 때문에 열차성능해석 계산시 열차의 견인, 제동 특성이 비선형이기 때문에 해석적인 방법으로 해를 구하는데 어려움이 많은 경제운전 문제를 운행 시간 여유분을 고려하여 에너지 소비를 최소화하는 운전 모형을 제시한다. 경제운전모형을 한국형 고속열차에 적용하여 그 타당성을 입증하였다.

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An Evolutionary Hybrid Algorithm for Control System Analysis

  • Sulistiyo;Nakao Zensho;Wei, Chen-Yen
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.535-538
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    • 2003
  • We employ Genetic Programming (GP) which is optimized with Simulated Annealing (SA) to recognize characteristic of a plan. Its result is described in Laplace function. The algorithm proceeds with automatic PID designs for the plant.

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Priority-based Genetic Algorithm for Bicriteria Network Optimization Problem

  • Gen, Mitsuo;Lin, Lin;Cheng, Runwei
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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    • pp.175-178
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    • 2003
  • In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

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