• 제목/요약/키워드: auto-tuning PID control

검색결과 101건 처리시간 0.026초

무인항공기 작동기 컨트롤러를 위한 퍼지 자동 이득 조정 PID 제어 연구 (Research of Fuzzy Auto gain tuning control to apply actuator controller of Unmaned Aerial Vehicle)

  • 김태완;백진욱;이형철
    • 한국항행학회논문지
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    • 제13권6호
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    • pp.813-819
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    • 2009
  • 무인항공기의 에일러론 및 플랩, 엘리베이터 등을 제어하기위한 작동기들은 구조적으로 Time variant한 비선형적인 특성을 가지고 있을 뿐 아니라, 비행 중에 풍향 및 풍량에 따라 모델링하기 힘든 외란이 발생할 경우가 많이 발생하기 때문에 우수한 제어성능을 보이는 제어기 설계에 많은 어려움이 있었다. 본 논문에서는 기존의 PID 제어기의 장점을 그대로 살리면서 실시간으로 변화하는 시스템에 adaptive하게 대응할 수 있고 Auto gain tuning을 이용하여 개발자의 시간과 노력을 현저히 줄일 수 있는 Fuzzy Auto gain tuning PID 제어 알고리즘을 비행체 Actuator 제어에 적용한 연구내용을 기술하였다.

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시간지연을 가진 발전소 제어시스템의 자동동조를 위한 System identification 방법 (System identification method for the auto-tuning of power plant control system with time delay)

  • 윤명현;신창훈;박익수
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.1008-1011
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    • 1996
  • Most control systems of power plants are using classical PID controllers for their process control. In order to get the desired control performances, the correct tuning of PID controllers is very important. Sometimes, it is necessary to retune PID controllers after the change of system operating condition and system design change, etc. Commercial auto-tuning controllers such as relay feedback controller can be used for this purpose. However, using these controllers to the safety-critical systems of nuclear power plants may be cause of unsafe operation, because they are using test signals for tuning. A new system identification auto-tuning method without using test signal has been developed in this paper. This method uses process input/output signals for system identification of unknown control process. From the model information of control process which was obtained from system identification approach, the optimal PID parameters can be calculated. The method can be used in the safety-critical systems because it is not using test signals during system modeling process.

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로봇 시스템에 대한 PID 궤적추종 제어기의 자동 성능동조 (Automatic Performance Tuning of PID Trajectory Tracking Controller for Robotic Systems)

  • 최영진
    • 제어로봇시스템학회논문지
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    • 제10권6호
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    • pp.510-518
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    • 2004
  • The PID trajectory tracking controller for robotic systems shows performance limitation imposed by inverse dynamics according to desired trajectory. Since the equilibrium point can not be defined for the control system involving performance limitation, we define newly the quasi-equilibrium region as an alternative for equilibrium point. This analysis result of performance limitation can guide us the auto-tuning method for PID controller. Also, the quasi-equilibrium region is used as the target performance of auto-tuning PID trajectory tracking controller. The auto-tuning law is derived from the direct adaptive control scheme, based on the extended disturbance input-to-state stability and the characteristics of performance limitation. Finally, experimental results show that the target performance can be achieved by the proposed automatic tuning method.

온도제어용 자동동조 PID 제어기 설계와 RTP에의 적용 (Development of auto-tuning PID controller for Temperature Control systems and Its Application to Rapid Thermal Processor)

  • 임재식;이영일
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.62-62
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    • 2000
  • An auto-tuning PID controller which is adequate for temperature control is developed based on relay-control and pole-placement Using the critical frequency which is obtained from relay-control parameters of assumed model are identified. Pole/zero-placement PID controller is designed for the identified model. The desired pole/zeros are determined so that the closed-loop has overshoot free step response. The developed auto-tuning PID controller was successfully applied to the temperature control of RTP.

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On the Auto Tuning of Fuzzy PID Controller

  • Kim, Yoon-Sang;Oh, Hyun-Cheol;Ahn, Doo-Soo
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.57-62
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    • 1998
  • This paper presents an auto tuning method of PID controller based on the application of fuzzy logic. The proposed method combined the principles of PID control with fuzzy control, which cam considerably improve the performance index of PID controller. Simulation results show that higher performance and accuracy of overall system for desired value is achieved with our manner when compared to widely-used conventional tuning method.

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Vibration Isolation Control using PSO Algorithm for Auto-tuning of PID Parameters

  • Oh, Se-Boung;Park, Chang-Su;Bang, Hyo-Choong
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1380-1385
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    • 2004
  • In this paper, auto-tuning technique of the PID controller gain by particle swarm optimization algorithm is presented. PID controller is easy to implement to numerous control systems. After PID gain tuning is completed, its result could be implemented to control spacecraft vibration such as jitter that is high frequency vibration usually over 10Hz. The off-line PID controller tuning is done under system nonlinearities and uncertainties existence, then its result is applied to control experiment device to prove the PSO efficiencies.

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시간 지연 릴레이 피드백을 이용한 자동동조 디지털 PID 제어기의 설계 (Design of a Auto-Tuning Digital PID Controller using Relay feedback and Time Delay)

  • 류경모;박정일
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.109-109
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    • 2000
  • In process industries, more than 90% of the control loops have PID controller. Futhermore, the most control systems are using classical PID controllers for their process control. Various auto-tuning methods of PID gains using relay-feedback are presented recently. In order to get the desired control performance, the correct tuning of PID controller is very important. This paper suggests how to tune of digital PID gains using information for both the Nyquist critical point by conventional method and another point by the relay feedback and hidden time-delay term. Simulation results show that the proposed controller has better performance than the conventional method.

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PID auto-tuning controller design via fuzzy logic

  • He, Wei;Yu, Tian;Zhai, Yujia
    • 한국융합학회논문지
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    • 제4권4호
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    • pp.31-40
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    • 2013
  • PID auto-tuning controller was designed via fuzzy logic. Typical values such as error and error derivative feedbackwere changed as heuristic expressions, and they determine PID gain through fuzzy logic and defuzzification process. Fuzzy procedure and PID controller design were considered separately, and they are combined and analyzed. Obtained auto-tuning PID controller by Fuzzy Logic showed the ability for less than 3rd order plant control.

조향형 이동로봇을 위한 PID 이득 자동 튜닝에 관한 연구 (A Study on PID Gain Auto Tuning for Steering Type mobile robot)

  • 정세영;양태규
    • 한국위성정보통신학회논문지
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    • 제11권4호
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    • pp.39-43
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    • 2016
  • 본 논문은 조향구조를 갖는 이동로봇의 조향 제어를 위해 PID 제어기의 이득을 튜닝 방법을 제안한다. PID 이득을 설정하는 다양한 방법들이 제시되고 연구되고 있다. 이득은 지글러-니콜스의 계단형 입력으로부터 이득을 얻는 방법으로 얻어진 이득을 이동로봇에 적용하고 이를 시험하여 다시 2차 전달함수에 의해 새로운 이득을 계산하였다. 얻어진 새로운 이득으로 응답시간 및 유지오차율에 관한 실험을 수행하여 PID 자동 튜닝의 성능을 확인하였다. 유지시간, 응답시간 및 수렴시간에 대한 실험결과로 이동로봇의 조향 시스템에서 사용이 가능하고 응답 시간이 빠르게 도달할 수 있으며 안정하게 제어됨을 확인하였다.

자동동조(自動同調) 퍼지 앨고리즘을 사용한 유도전동기(誘導電動機) 구동(驅動)에 관한 연구(硏究) (The Study on IM Drive using a Auto-Tuning Fuzzy PID Control Algorithm)

  • 윤병도;김윤호;정재륜;김춘삼;채수형
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1992년도 하계학술대회 논문집 B
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    • pp.1242-1244
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    • 1992
  • This Paper deals with a Auto-Tuning Fuzzy PID Controller used in real time and its application for induction motor. The control strategy of the controller is able to develop and improve automatically. The new Auto-Tuning Fuzzy PID Control algorithm which modifies the fuzzy control decision table is presented in this paper. It can automatically refine an initial approximate set of fuzzy rules. The possibility of applying fuzzy algorithms in faster response, and more accurate was compared with other industrial processes, such as AC Motor driver. The performance of Proportional_Integral Derivative(PID) control and this fuzzy controllers is compared in terms of steady_state error, settling time, and response time. And then, Limitations of fuzzy control algorithms are also described.

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