• 제목/요약/키워드: Data Controller

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Adaptive Control of Robot Manipulator using Neuvo-Fuzzy Controller

  • Park, Se-Jun;Yang, Seung-Hyuk;Yang, Tae-Kyu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.161.4-161
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    • 2001
  • This paper presents adaptive control of robot manipulator using neuro-fuzzy controller Fuzzy logic is control incorrect system without correct mathematical modeling. And, neural network has learning ability, error interpolation ability of information distributed data processing, robustness for distortion and adaptive ability. To reduce the number of fuzzy rules of the FLS(fuzzy logic system), we consider the properties of robot dynamic. In fuzzy logic, speciality and optimization of rule-base creation using learning ability of neural network. This paper presents control of robot manipulator using neuro-fuzzy controller. In proposed controller, fuzzy input is trajectory following error and trajectory following error differential ...

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활성오니 공정의 퍼지 모델 베이스형 제어기의 설계 (Design of fuzzy model-based controller for activated sludge process)

  • 김현기;오성권;황희수;우광방
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.922-927
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    • 1991
  • This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

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다각 보행 로보트를 위한 서보제어기 (A servo controller for the multi-legged walking robot)

  • 이연정;여인택;박찬웅
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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    • pp.137-141
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    • 1988
  • A sampled data controller for the quadruped walking robot is presented. To provide systematic design procedure, the relation between PI gain of velocity controller and sampling rate is analyzed with the ISE performance index and the time responses. The position controller for one-leg, 3-axis, was developed under consideration of compactness and expendability. And several experiments were performed.

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최적 제어 이론을 이용한 서어보 메카니즘의 PID 제어기 설계 (A design of PID controller for servomechanism using optimal control theory)

  • 최중락;김재환;김영수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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    • pp.488-492
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    • 1986
  • This paper presents a design method for PID controller using optimal control theory. The procedures of the applied method consist of (1) sampling the system response to the test signal, (2) processing the sampled data using RPE method to identify the parameters of the plant, (3) calculating the optimal value of the PID controller parameters using LQ theory. This controller is implemented on the digital computer and applied to real servomechanism, yielding satisfactory result.

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앞먹임 신경회로망 제어기를 이용한 자기부상 실험시스템의 제어 (Control of an experimental magnetic levitation system using feedforward neural network controller)

  • 장태정;이재환
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.1557-1560
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    • 1997
  • In this paper, we have built an experimental magnetic levitation system for a possible use of control education. We have give a mathermatical model of the nonlinear system and have shown the stability region of the linearized system when it is controlled by a PD controller. We also proposed a neural network control system which uses a neural network as a feedforward controller thgether with a conventional feedback PF controller. We have generated a desired output trajectory, which was designed for the benefit of the generalization of the neural network controller, and trained the desired output trajectory, which was desigend for the benefit of the generalization of the neural netowrk controller, and trained a neural network controller with the data of the actual input and the output of the system obtained by applying the desired output trajectroy. A good tracking performance was observed for both the desired trajectiories used and not used for the neural network training.

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Intelligent adaptive controller for a process control

  • Kim, Jin-Hwan;Lee, Bong-Guk;Huh, Uk-Youl
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.378-384
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    • 1993
  • In this paper, an intelligent adaptive controller is proposed for the process with unmodelled dynamics. The intelligent adaptive controller consists of the numeric adaptive controller and the intelligent tuning part. The continuous scheme is used for the numeric adaptive controller to avoid the problems occurred in the discrete time schemes. The adaptive controller is adopted to the process with time delay. It is an implicit adaptive algorithm based on GMV using the emulator. The tuning part changes the design parameters in the control algorithm. It is a multilayer neural network trained by robustness analysis data. The proposed method can improve the robustness of the adaptive control system because the design parameters are tuned according to the operating points of the process. Through the simulation, robustnesses are shown for intelligent adaptive controller. Finally, the proposed algorithms are implemented on the electric furnace temperature control system. The effectiveness of the proposed algorithm is shown from experiments.

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조향감을 고려한 자동차용 전동조향장치의 퍼지제어기의 개발 (Development of Fuzzy Controller for Electric Power Steering Considering Steering Feel)

  • 한창수;이명호;박호
    • 한국공작기계학회논문집
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    • 제11권2호
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    • pp.50-58
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    • 2002
  • The test method using simulator to objectively measure the steering feel from several drivers was proposed. It has also described the ideas to analyse the principal factors affecting the steering feel of the driver using the correlation analysis of the measured data and the questionnaire. Proportional Derivative(PD) controller has been used to measure the steering feel, and the control parameters have been selected to obtain the optimal steering feel. Membership frictions of Sugeno fuzzy model are constructed from the assist torque values calculated from PD controller at each steering state. Moreover to verify the performance, this fuzzy controller has been compared with the another fuzzy controller of which membership frictions are derived from the knowledge of drivers. As a result it can be concluded that the proposed fuzzy controller improves the steering feel at each steering state more than any other conventional methods.

유전알고리듬에 의한 조준경 시스템의 신경망제어기 설계 (Neuro-genetic controller design of the line of sight system)

  • 이승수;장준오;전기준
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.956-959
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    • 1996
  • In this study, we propose a neuro-genetic controller combined with a linear controller in parallel to improve the tracking performance of the Line of Sight(LOS) stabilization system and reject the effect of disturbances. A Genetic Algorithm(GA) is used to optimize weights of the neuro-genetic controller since this algorithm can search a global minimum without derivatives or other auxiliary knowledge. The LOS system is very complex and has limited measurable output data. Under these specific circumstances GA solves many problems that other training methods have. Computer simulation results show that the, proposed controller makes better tracking response and rejection of disturbance than a linear controller.

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실험적 접근을 통한 제어기 설계 (Controller design with experimental approach)

  • 신시중;전기준
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.200-205
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    • 1992
  • The classical control theory has been developed successfully for the design of a system controller and has evolved continually. Even though sophisticated simulation techniques and software packages are available, there is still some difficulty in the design of a complex system controller at the desk. So the trial and error method is sometimes used to design a new controller, but it requires excess time and cost. This paper suggests a controller design method through the experimental approach. The basic concept is to adjust gradually the design parameters of the controller to the simulation results and experimental data of a similar real system. This method will be a very useful and easy way to design an accurate and/or optimal controller for a real plant while reducing time and giving a good solution at a reasonable cost.

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변조함수를 이용하는 하이브리드 퍼지 논리 제어기 (Hybrid Fuzzy Logic Controller using Modulation Function)

  • 이평기
    • 한국산업융합학회 논문집
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    • 제6권4호
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    • pp.393-399
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    • 2003
  • In this paper, a self-organizing fuzzy logic controller with hybrid structure is proposed. The structure of the proposed method is composed of a basic fuzzy logic controller and the FARMA SOC(Fuzzy Autoregressive Moving Average Self-organizing Controller). The self-organizing cntroller with hybrid structure has advantage over the FARMA controller as follows. The proposed controller improves poor performance due to the lack of I/O data to calculate predictive output. I executed some computer simulations on the regulation problem of an inverted pendulum system and compared the results of the proposed method with those of the FARMA SOC method.

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