• Title/Summary/Keyword: Logic Rules

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Fuzzy Variable Structure Control System for Fuel Injected Automotive Engines (연료분사식 자동차엔진의 퍼지가변구조 제어시스템)

  • Nam, Sae-Kyu;Yoo, Wan-Suk
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.7 s.94
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    • pp.1813-1822
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    • 1993
  • An algorithm of fuzzy variable structrue control is proposed to design a closed loop fuel-injection system for the emission control of automotive gasoline engines. Fuzzy control is combined with sliding control at the switching boundary layer to improve the chattering of the stoichiometric air to fuel ratio. Multi-staged fuzzy rules are introduced to improve the adaptiveness of control system for the various operating conditions of engines, and a simplified technique of fuzzy inference is also adopted to improve the computational efficiency based on nonfuzzy micro-processors. The proposed method provides an effective way of engine controller design due to its hybrid structure satisfying the requirements of robustness and stability. The great potential of the fuzzy variable structure control is shown through a hardware-testing with an Intel 80C186 processor for controller and a typical engine-only model on an AD-100 computer.

The development of fuzzy reasoning tool for the support design of servo system (서보 제어계 설계지원을 위한 퍼지추론 TOOL의 개발)

  • 노창주;홍순일
    • Journal of Advanced Marine Engineering and Technology
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    • v.19 no.4
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    • pp.72-78
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    • 1995
  • The diffusion of fuzzy logic techniques into real applications requires specific software supports which save development time and reduce the programming effort. But we has been lack of a tool devoted to support the design of fuzzy controllers. In this paper, on the basis of the general fuzzy set and .alpha.-cut set decomposition of fuzzy sets, a set of fuzzy reasoning tool(FRT) devoted to support the design of fuzzy dontroller for servo systems is developed. The major features of this tool are: 1) It supports users to analyze fuzzy ingerence status based on input deta and expected results by three-D graphic display. 2) It supports users to prepare input data and expected result. 3) It supports users to tuned scaling factor of membership functions, rules and fuzzy inference. The paper shows how the suggested design tools are suitable to give a consistent answer to the tuning of fuzzy control system. This FRT is expected to exert good performance and devoted to support which the design of fuzzy controller is illustrated in the servo systems.

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A Design of Fuzzy Precompensated PID Controller for Load Frequency Control of Power System using Genetic Algorithm (유전 알고리즘을 이용한 전력계통의 부하주파수 제어를 위한 퍼지 전 보상 PID 제어기 설계)

  • Chung, Mun-Kyu;Wang, Yong-Peel;Lee, Jeong-Phil;Chung, Hyeng-Hwan
    • Proceedings of the KIEE Conference
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    • 1999.11b
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    • pp.153-156
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    • 1999
  • In this paper, we design a GA-fuzzy precompensated PID controller for the load frequency control of two-area interconnected power system. Here, a fuzzy precompensated PID controller is designed as a fuzzy logic-based precompensation approach for PID controller. This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PID controller. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor membership function and control rules.

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Self-Organizing Fuzzy Controller Using Command Fusion Method and Genetic Algorithm

  • Na, Young-Nam;Choi, Wan-Gyu;Lee, Sung-Joo
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.2 no.3
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    • pp.242-247
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    • 2002
  • According to increase of the factory-automation(FA) in the field of production, the importance of the autonomous guided vehicle's(AGV) role has also increased. This paper is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an behavior-based system evolving by itself is also being considered. In this Paper, we constructed an active and effective AGV fuzzy controller to be able to carry out self-organization. To construct it, we tuned suboptimally membership function using a genetic algorithm(GA) and improved the control efficiency by self-correction and the generation of control rules.

A Fuzzy Approach to Social Worker's Turnover Intention

  • Jang, Yun-Jeong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.10 no.3
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    • pp.165-169
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    • 2010
  • This study seeks to find the factors associated with social workers' turnover intention and show us how to manage turnovers by looking for some rules affecting turnover intentions. Our investigation surveying 331 social workers reveals that social workers' turnover intentions are affected by organizational commitment, job satisfaction, and burnout. Our pattern analyses using fuzzy ID3 show that the higher their commitment, the higher their job satisfaction stemming from promotion opportunities, rewards, and personal relations with peers and bosses. In addition, turnover intentions decreases (even if burnouts--the job-related stress--are very serious) when organizational commitment increases. We come to understand that organizational commitment could be a more important variable than job satisfaction and burnouts. Such results suggest that it would be necessary to consider how to improve social workers' organization-wide commitment rather than satisfaction and burnout related to jobs and environments.

Self-organizing Networks with Activation Nodes Based on Fuzzy Inference and Polynomial Function (펴지추론과 다항식에 기초한 활성노드를 가진 자기구성네트윅크)

  • 김동원;오성권
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.15-15
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    • 2000
  • In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.

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On-line Fuzzy Performance Management of Profibus Networks (지능제어를 이용한 Profibus Network의 온라인 성능 관리)

  • Lee, Kyung-Chang;Kang, Song;Kim, Tae-Jun;Lee, Seok
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.117-117
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    • 2000
  • This paper presents experimental results for peformance management of a Profibus-FMS network. The performance management alms to maintain a uniform level of network performance at all stations under changing network traffic. The performance management algorithm monitors the performance of individual network stations and commands the stations to change their timer values in order to have comparable performance at all stations. In order to determine the amount of timer change, the algorithm employs a set of fuzzy rules. This algorithm has been evaluated on a Profibus network

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Development of Rule-Based Knowledge Representation Supporting Tool for Design Digital Moister System (설계 디지털 마이스터 시스템 구축을 위한 규칙 기반 지식 표현 지원 도구 개발)

  • Nam S.H.;Kang H.W.;Lee W.;Suh H.W.;Choi H.J.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.633-634
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    • 2006
  • Recently we started a development of the digital meister expert system for the product design supporting in manufacturing industry. Knowledge representation is of major importance in digital moister expert system. This rule-based expert system-knowledges are designed for a certain type of knowledge representation such as rules or logic. The way in which a rule-based expert system represents knowledge affects the development, efficiency, speed, and maintenance. Eventually, this digital moister system is used to the engineer in manufacturing industry for the process control, production management and system management. In this paper, we propose the digital moister system knowledge representation method for product design supporting in manufacturing industry and we present introduction and contents of rule-based knowledge representation supporting tool.

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Speed Estimation and Control of IPMSM Drive with HAI Controller (HAI 제어기에 의한 IPMSM 드라이브의 속도 추정 및 제어)

  • Lee Hong-Gyun;Lee Jung-Chul;Chung Dong-Hwa
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.4
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    • pp.220-227
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    • 2005
  • This paper presents hybrid artificial intelligent(HAI) controller based on the vector controlled IPMSM drive system. And it is based on artificial technologies that adaptive neural network fuzzy(A-NNF) is to speed control and artificial neural network(ANN) is to speed estimation. The salient feature of this technique is the HAI controller The hybrid action tolerates any inaccuracies in the fuzzy logic assignment rules or in the neural network stationary weights. Speed estimators using feedforward multilayer and artificial neural network(ANN) are compared. The back-propagation algorithm is easy to derived the estimated speed tracks precisely the actual motor speed. This paper presents the theoretical analysis as well as the simulation results to verify the effectiveness of the new hybrid intelligent control.

Design of GA-Fuzzy Precompensator for Enhancement of Pourer System Stability (전력시스템의 안정도 향상을 위한 GA-퍼지 전 보상기 설계)

  • Jeong, Hyeong-Hwan;Jeong, Mun-Gyu;Lee, Jeong-Pil
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.2
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    • pp.83-92
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    • 2002
  • In this paper, we design a GA-fuzzy precompensator for enhancement of power system stability. Here, a fuzzy prerompensator is designed as a fuzzy logic-based precompensation approach for Power System Stabilizer(PSS). This scheme is easily implemented simply by adding a fuzzy precompensator to an existing PSS. And we optimize the fuzzy precompensator with a genetic algorithm for complements the demerit such as the difficulty of the component selection of fuzzy controller, namely, scaling factor, membership function and control rules. Simulation results show that the proposed control technique is superior to a conventional PSS in dynamic responses over the wide range of operating conditions and is convinced robustness and reliableness in view of structure.