• 제목/요약/키워드: inference Control

검색결과 662건 처리시간 0.031초

PDA를 이용한 이동로봇 제어 (PDA-based Supervisory Control of Mobile Robots)

  • 정성호;김성주;김용택;전홍태
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2002년도 춘계학술대회 및 임시총회
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    • pp.105-108
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    • 2002
  • This paper represents the mobile robot control system remote controlled by PDA(personal digital assistance). So far, owing to the development of internet technologies, lots of remote control methods through internet have been proposed. To control a mobile robot through internet and guide it under unknown environment, We propose a control method activated by PDA. In a proposed system, PDA acts as a user interface to communicate with notebook as a controller of the mobile robot system using TCP/IP protocol, and the notebook controls the mobile robot system. The information about the direction and velocity of the mobile robot feedbacks to the PDA and the PDA send new control method produced from the fuzzy inference engine.

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Verification of a hybrid control approach for spacecraft attitude stabilization through hardware-in-the-loop simulation

  • Kim, Sung-Woo;Park, Sang-Young
    • 한국우주과학회:학술대회논문집(한국우주과학회보)
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    • 한국우주과학회 2011년도 한국우주과학회보 제20권1호
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    • pp.32.2-32.2
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    • 2011
  • State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

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$\alpha$-레벨 퍼지집합 분해에 의한 직류 서보제어용 퍼지 PI+PD 로직회로 구현 (Implemented of Fuzzy PI+PD Logic circuits for DC Servo Control Using Decomposition of $\alpha$-level fuzzy set)

  • 홍정표;원태현;정종원;이영수;이상무;홍순일
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2008년도 하계학술대회 논문집
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    • pp.127-129
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    • 2008
  • This paper describes a method of approximate reasoning for fuzzy control of servo system, based on decomposition of -level fuzzy sets. It is propose that logic circuits for fuzzy PI+PD are a body from fuzzy inference to defuzzificaion in cases where the output variable u directly is generated PWM. The effectiveness for robust and faster response of the fuzzy control scheme is verified for a variable parameter by comparison with a PID control and fuzzy control. A position control of DC servo system with a fuzzy logic controller successfully demonstrated.

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퍼지 PID 제어를 이용한 추종 제어기 설계 (Design of Fuzzy PID Controller for Tracking Control)

  • 김봉주;정정주
    • 제어로봇시스템학회논문지
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    • 제7권7호
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    • pp.622-631
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    • 2001
  • This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional PID controller.

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성능평가에 의한 퍼지제어시스템 동조 (Fuzzy control system tuning by performance evaluation)

  • 정헌;정창규;고낙용;김영동;최한수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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    • pp.682-684
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    • 1995
  • The most effective way to improve the performance of a fuzzy controller may be to optimize look-up values. Look-up values are derived from processes used input-output scale factors, membership functions, rule base, fuzzy inference method and defuzzification. It is powerful way to modify or organize look-up table values. In this paper, We propose the look-up values self-organizing fuzzy controller(LSOFC). We use the plus-minus tuning method(PMTM), scanning values through the processes of addition and subtraction. We show the efficiency of this LSOFC by the results of simulation for nonlinear time-varying plant with unmodelled dynamics.

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뉴로 퍼지망을 이용한 비선형 시스템 제어 (Control of the Nonlinear System Using Neuro Fuzzy Network)

  • 김동훈;이영석;서보혁
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1073-1075
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    • 1996
  • This paper presents a neuro fuzzy system(NFS) for implementing fuzzy inference system with a monotonic membership function. The modeling and control of a discrete nonlinear system using a NFS is described. The membership function parameters of a identifier and controller are adjusted by back-propagation algorithm. These identifier and controller is constructed to proposed NFS. A on-line identification and control are accomplished by this NFS. A controller is gived information of the system, that is variation of the system output according to that of the control input by a identifier. A controller makes control input in order to control discrete-time nonlinear system. A Simulation is presented to demonstrate the efficiency of a suggested method.

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소형 터보제트 엔진의 서지 제어를 위한 퍼지추론 기법 (Surge Control of Small Turbojet Engines with Fuzzy Inference Method)

  • 지민석;홍승범
    • 한국항공운항학회지
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    • 제17권4호
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    • pp.1-7
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    • 2009
  • The surge control system in unmanned turbojet engine must be capable of accounting uncertainties from engine transient conditions, random fluctuations of key parameters such as air pressure and fuel flow and engine modeling errors. In this paper, taking into consideration of its effectiveness as well as system stability, a fuzzy PI controller is proposed. The role of the fuzzy PI controller is to stabilize the unmanned aircraft upon occurring unexpected engine surge. The proposed control scheme is proved by computer simulation using a linear engine model. The simulation results on the state space model of a small turbojet engine illustrate the proposed control system achieves the desired performance.

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SIMULATOR FOR EVALUATION OF VARIOUS FUZZY CONTROL METHODS

  • Hayashi, Kenichiro;Muta, Itsuya;Hoshino, Tsutomu;Ohtsubo, Akifumi
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1993년도 Fifth International Fuzzy Systems Association World Congress 93
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    • pp.949-952
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    • 1993
  • As well-known, fuzzy control has been recognized to be of great usefulness in many engineering fields. However, the present design methods of fuzzy control systems depend on trial and error the thing that limits its usefulness. Therefore, an effective and convenient support tools for design and evaluation are greatly needed as well as the establishment of the design methods and guidling. From these backgrounds, we have developed a fuzzy control simulator[1, 2] which has various fuzzy control methods such as "direct method", "indirect method" and "fuzzy-PID method". This paper deals especially with the "direct method" function of the simulator. The simulator was developed for personal computers and programed in C language.

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Multiple Reward Reinforcement learning control of a mobile robot in home network environment

  • Kang, Dong-Oh;Lee, Jeun-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.1300-1304
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    • 2003
  • The following paper deals with a control problem of a mobile robot in home network environment. The home network causes the mobile robot to communicate with sensors to get the sensor measurements and to be adapted to the environment changes. To get the improved performance of control of a mobile robot in spite of the change in home network environment, we use the fuzzy inference system with multiple reward reinforcement learning. The multiple reward reinforcement learning enables the mobile robot to consider the multiple control objectives and adapt itself to the change in home network environment. Multiple reward fuzzy Q-learning method is proposed for the multiple reward reinforcement learning. Multiple Q-values are considered and max-min optimization is applied to get the improved fuzzy rule. To show the effectiveness of the proposed method, some simulation results are given, which are performed in home network environment, i.e., LAN, wireless LAN, etc.

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범용의 퍼지 하드웨어 설계 (A Design of the General-Purpose Fuzzy Hardware)

  • 김용태;이승하;이윤정
    • 전자공학회논문지B
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    • 제31B권7호
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    • pp.149-158
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    • 1994
  • Recently the fuzzy control is widely used as a tool for constructing automatic control systems which can replace the manual operation of large-scale nonlinear plants. In most applications of the fuzzy control however it is hard to meet the requirement of the operation time. In some real-time control the fuzzy control scheme requires too much computing time for fuzzification inference and defuzzification. To reduce the computing time there may be two alternatives the development of a new operation algorithm and the design of high-speed fuzzy hardware. In this paper to solve the problem of reducing the fuzzy operation time we propose a new high-speed fuzzy hardware scheme which has merits of its generality and extensibility. Finally we verify the proposed fuzzy hardware.

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