• 제목/요약/키워드: PI algorithm

검색결과 557건 처리시간 0.028초

Fuzzy rule을 이용한 공압 서보 제어 알고리즘의 개발 (Development of pneumatic servo control algorithm using fuzzy rule)

  • 박상덕;정규원;염영일
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 22-24 Oct. 1991
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    • pp.1127-1132
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    • 1991
  • Pneumatic control system has been used mainly for endpoint position control because of the compressibility, viscosity and low output stiffness of air which causes nonlinear flow characteristics. In this paper, pneumatic position control algorithms using fuzzy rule were developed to achieve faster and more stable response than conventional PI control algorithm. The performances of the proposed algorithms were compared by computer simulations with them of PI controller. From those simulations it was shown that the proposed algorithms are more efficient about settling time, steady state error and overshoot than PI control algorithm.

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주파수 영역에서의 모델 축소를 이용한 PID 제어기의 동조 알고리즘 (Tuning Algorithm for PID Controller Using Model Reduction in frequency Domain)

  • 조준호;최정내;황형수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2001년도 하계학술대회 논문집 D
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    • pp.2114-2116
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    • 2001
  • Model reduction from high order systems to low order systems in frequency domain is considered four point (${\angle}$G(jw)=0, - ${\pi}/2$, ${\pi}$, and -3${\pi}$/2) instead of two point (${\angle}$G(jw) = - ${\pi}$/2,- ${\pi}$) of existing method in Nyquist curve. The Performances of reduced order model by proposed approach is similar to original model. In this paper, we proposed a new tuning algorithm for PID controller using model reduction in frequency domain. Simulations for some examples with varies dynamic characteristics are provided to show the effectiveness of the proposed tuning algorithm for PID controller using model reduction.

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멀티형 히트펌프 전자팽창밸브의 디더 신호를 적용한 과열도 제어 (EEV Superheat Control of a Multi-type Heat Pump by Using Dither Signal)

  • 한도영;표수환
    • 설비공학논문집
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    • 제14권11호
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    • pp.948-953
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    • 2002
  • The electronic expansion valve (EEV) may be used to control the refrigerant flow rate for the multi-type heat pump. Stepping motor driven EEV may precisely control the refrigerant flow rate to meet each internal load requirement. To control the EEV, PI algorithm may be used. But the hysteresis of EEV deteriorates the performance of superheat control. To reduce the performance degradation, the PI algorithm along with the dither signal may be used. The dither signal, with about 10 times higher frequency than the system crossover frequency and about 10 times larger magnitude than the deadband of hysteresis, was selected for the superheat control of EEV. Experimental results showed the improvement of EEV control by adding the dither signal to the PI algorithm.

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유리 용해로 온도 제어를 위한 퍼지 로직과 PI 제어기의 복합형 제어 알고리듬 (A hybrid algorithm of fuzzy logic and conventional PI controller for the temperature control of glass melting furnace)

  • 문운철;김흥식;박영문
    • 제어로봇시스템학회논문지
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    • 제4권2호
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    • pp.215-219
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    • 1998
  • This paper presents a practical application of fuzzy logic control to temperature control of glass melting furnace. Due to the characteristics of glass melting furnace, a hybrid algorithm of conventional PI controller and fuzzy logic controller is proposed and discussed. Practical implementation results of the production furnace showed the effectiveness of the proposed control algorithm.

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새로운 축소 모델을 이용한 Smith-Predictor 제어기 설계 (Smith-Predictor Controller Design Using New Reduction Model)

  • 최정내;조준호;황형수
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권1호
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    • pp.9-15
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    • 2003
  • To improve the performance of PID controller of high order systems by model reduction, we proposed two model reduction methods. One, Original model with two point $({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$ in Nyquist curve used gradient base method and genetic algorithm. The other, Original model without two point$({\angle}G(jw)=\;-{\pi}/2,\;-{\pi})$in Nyquist curve used to add very small dead time. This method has annexed very small dead time on the base model for reduction, and we remove it after getting the reduced model, and , we improved Smith-predictor for a dead-time compensator using genetic algorithms. This method considered four points$({\angle}G(jw)=0,\;-\pi/2,\;-\pi,\;-3\pi/2)$ in the Nyquist curve to reduce steady state error between original and reduced model. It is shown that the proposed methods have more performance than the conventional method.

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Fuzzy Gain Scheduling of Velocity PI Controller with Intelligent Learning Algorithm for Reactor Control

  • Kim, Dong-Yun;Seong, Poong-Hyun
    • 한국원자력학회:학술대회논문집
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    • 한국원자력학회 1996년도 추계학술발표회논문집(1)
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    • pp.73-78
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    • 1996
  • In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.

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콜러스터링 퍼지알고리즘을 이용한 영구자석 동기전동기 구동용 PI 제어기 설계 (PI Controller Design for Permanent Magnet Synchronous Motor Drives Using Clustering Fuzzy Algorithm)

  • 권정진;한우용
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2004년도 추계학술대회 논문집 전기기기 및 에너지변환시스템부문
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    • pp.182-184
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    • 2004
  • This paper presents a PI controller tuning method for high performance permanent magnet synchronous motor (PMSM) drives under load variations using clustering fuzzy algorithm. In many speed tracking control systems PI controller has been used due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, the PI controller parameters are modified during operation by clustering fuzzy method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained Simulation results show the usefulness of the proposed controller.

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시스템 안정도 향상을 위하여 SVC를 포함한 전력계통의 최적 GA-PI 제어기 설계 (A Design of Optimal GA-PI Controller of Power System with SVC to Improve System Stability)

  • 정형환;허동렬;이종민;주석민
    • Journal of Advanced Marine Engineering and Technology
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    • 제24권2호
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    • pp.63-71
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    • 2000
  • This paper deals with a systematic approach to GA-PI controller design for static VAR compensator(SVC) using genetic algorithm(GA) to improve system stability. Genetic algorithms(GAs) are search algorithms based on the mechanics of natural selection and natural genetics. To verify the validity of the proposed method, investigated damping ratio of the eigenvalues of the electro-mechanical modes system with and without SVC. Also, we considered dynamic response of terminal speed deviation and terminal voltage deviation by applying a power fluctuation at heavy load, normal load and light to verify the robustness of the proposed. Thus, we proved usefulness of GA-PI controller design to improve the stability of single machine-bus with SVC system.

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Design of Fuzzy Scaling Gain Controller using Genetic Algorithm

  • Hyunseok Shin;Lee, Sungryul;Hyungjin Kang;Cheol Kwon;Park, Mignon
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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    • pp.474-478
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    • 1998
  • This paper proposes a method which can resolve the problem of exisiting fuzzy PI controller using optimal scaling gains obtained by genetic algorithm. The new method adapt a fuzzy logic controller as a high level controller to perform scaling gain algorithm between two pre-determined sets.

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Optimization of PI Controller Gain for Simplified Vector Control on PMSM Using Genetic Algorithm

  • Jeong, Seok-Kwon;Wibowo, Wahyu Kunto
    • 동력기계공학회지
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    • 제17권5호
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    • pp.86-93
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    • 2013
  • This paper proposes the used of genetic algorithm for optimizing PI controller and describes the dynamic modeling simulation for the permanent magnet synchronous motor driven by simplified vector control with the aid of MATLAB-Simulink environment. Furthermore, three kinds of error criterion minimization, integral absolute error, integral square error, and integral time absolute error, are used as objective function in the genetic algorithm. The modeling procedures and simulation results are described and presented in this paper. Computer simulation results indicate that the genetic algorithm was able to optimize the PI controller and gives good control performance of the system. Moreover, simplified vector control on permanent magnet synchronous motor does not need to regulate the direct axis component current. This makes simplified vector control of the permanent magnet synchronous motor very useful for some special applications that need simple control structure and low cost performance.