• Title/Summary/Keyword: Auto-Tuning Fuzzy PID Control

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An Auto-tuning of PID Controller using Fuzzy Performance Measure and Neural Network for Equipment System (전력설비시스템을 위한 퍼지 평가함수와 신경회로망을 사용한 PID제어기의 자동동조)

  • 이수흠;박현태;이내일
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.13 no.2
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    • pp.63-70
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    • 1999
  • This paper is proposed a new method to deal with the optimized auto-tuning for the Pill controller which is used to the process-control in various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade-approximated, then initial values are determined by the Ziegler-Nichols method. So we can find the parameters of Pill controller so as to minimize the fuzzy criterion function which includes the maximum overshoot, damping ratio, rising time and settling time. Finally, after studying the parameters of Pill controller by Backpropagation of Neural-Network, when we give new K, L, T values to Neural-Network, the optimized parameter of Pill controller is found by Neural-Network Program.rogram.

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Drive of Induction Motors Using a Pseudo-On-Line Fuzzy-PID Controller Based on Genetic Algorithm

  • Ahn, Taechon;Kwon, Yangwon;Kang, Haksoo
    • Transactions on Control, Automation and Systems Engineering
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    • v.2 no.2
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    • pp.85-91
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    • 2000
  • This paper proposes a novel method with pseudo-on-line scheme using the optimized look-up table based on the genetic algorithm which does not use the gradient and finds the global optimum of an un-constraint optimization problem. The technique is a pseudo-on-line method that optimally estimates the parameters of fuzzy PID(FPID) controller for systems with non-linearity, using the genetic algorithm. The proposed controller(GFPID) with the auto-tuning function is applied to the on-line and real-time control of speed at 3-phase induction motor, and its computer simulation is carried out. simulation results show that the proposed methodis more excellent that conventional FPID and PID controllers.

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Implementation of Temperature Measuring Sl Control System sing Fuzzy Theory (Fuzzy 이론을 이용한 온도 계측제어 시스템의 구현)

  • 박정훈;강문성;김윤호;유광렬
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.11a
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    • pp.282-286
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    • 1999
  • This paper describes the implementation of a fuzzy temperature measuring & control system to control the water temperature in plant. This system consisted of mainly three parts; sensing part, control part that includes a control algorithms introduced the fuzzy theory, and actuating part. The control algorithms of control part are utilized a look-up table method and firmware technique using one-chip microprocessor(89C52). For evaluating the performance of a fuzzy control system, the experiment results of a fuzzy controller are compared with these of a conventional PID controller which provides an auto-tuning function. The experiment results show that the proposed controller has a good control performance and is robust to external disturbance.

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The Optimal Design of HFC by means of GAs (유전자 알고리즘을 이용한 HFC의 최적설계)

  • 이대근;오성권;장성환
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.369-369
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    • 2000
  • Control system by means of fuzzy theory has demonstrated its robustness in applying to the high-order and nonlinear dynamic system in that it can utilizes the human expert knowledges in system design. In this paper, first, the design methodology of HFC combined PID controller with fuzzy controller by membership function of weighting coefficient is proposed. Second, Second, an auto-tuning algorithms utilizing the simplified reasoning method and genetic algorithms is presented to improve the performance of hybrid fuzzy controller. Especially, in order to obtain the optimal scaling factors and PID parameters of HFC using GA based on advanced initial individual, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The proposed HFC is evaluated and discussed in ITAE, overshoot and rising time to show applicability and superiority with simulation results.

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Parameter Identification with Fuzzy Inference and Speed Control of D.C Servo Motor (퍼지추론을 이용한 파라미터 식별 및 D.C 서보 모터의 속도제어)

  • Lee, Un-Cheol;Kim, Jong-Hoon;Lee, In-Hee;Nam, Moon-Hyon
    • Proceedings of the KIEE Conference
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    • 1995.07b
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    • pp.852-854
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    • 1995
  • This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

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Hybrid Fuzzy Controller Using GAs Based on Control Parameters Estimation mode (제어파라미터 추정모드기반 GA를 이용한 HFC)

  • Lee, Dae-Keun;Oh, Sung-Kwun;Jang, Sung-Whan
    • Proceedings of the KIEE Conference
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    • 2000.11d
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    • pp.700-702
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    • 2000
  • The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. In fuzzy controller which has been widely applied and used. in order to construct the best fuzzy rules that include adjustment of fuzzy sets, a highly skilled techniques using trial and error are required. To deal with such a problem, first, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller from each control output in steady state and transient state. Second, a auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller, utilizing the simplified reasoning method and genetic algorithms. In addition, to obtain scaling factors and PID Parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The HFCs are applied to the first-order second-order process with time-delay and DC motor Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed from performance indices.

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The Control of 3-Phase Induction Motor by Hybrid Fuzzy-PID Controller : Auto-Tuning of Parameters using Genetic Algorithms (하이브리드 퍼지-PID 제어기에 의한 3상 유도 전동기의 속도제어 : 유전자 알고리즘에 의한 파라미터의 자동 동조)

  • Kwon, Yang-Won;Ahn, Tae-Chon;Kang, Hak-Su;Yoon, Yang-Woong
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.794-796
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    • 1999
  • 본 논문에서는 3상 유도전동기의 속도를 제어하는데 기존 제어기의 문제점을 해결하고 최적화하기 위해서 유전자 알고리즘을 이용한 하이브리드 퍼지 -PID(HFPID) 제어기를 고안하고, 이에 대한 파라미터 설정 방법을 제안한다. 유도전동기의 제어는 지연시간이 길고, 비선형성이 강하며, 부하변동이 잦은 프로세스이기 때문에, 기존의 제어방식으로는 만족할만한 결과를 얻을 수 없다. 제안한 하이브리드 퍼지-PID 제어기는 PID 제어기의 장점인 과도기의 우수성과 퍼지 제어기의 장점인 정상기의 우수성을 퍼지 변수로 결합시켜 설계한다. 이 제어기에 유전자 알고리즘을 적용하여 최적의 퍼지 및 PID 파라미터를 설정하다. 그리고 이 제어기를 3상 유도전동기의 속도 제어에 응용한다. 또한 속도오차에 대한 룩업 표를 만들어 온라인 실시간 제어를 가능하게 한다. 이상의 과정을 3상 유도전동기에서 컴퓨터 시뮬레이션 하였다. 시뮬레이션 결과를 비교해 볼 때, 하이브리드 퍼지-PID 제어기는 기존의 제어기 보다 전동기의 속도 및 토크성분 전류 둥의 특성에서 우수한 성능을 보였다.

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Transient State Improvement of Three-Phase ZSI with the Input Feedforward and Fuzzy PI Controller (입력 피드포워드와 퍼지 PI제어기를 갖는 3상 ZSI의 과도상태 개선)

  • WU, Yan-Jun;Jung, Young-Gook;Lim, Young-Cheol
    • Proceedings of the KIPE Conference
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    • 2012.07a
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    • pp.359-360
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    • 2012
  • This paper proposes a scheme of auto-tuning fuzzy PI controller and input voltage feed forward to control the output voltage of a three-phase Z-source inverter (ZSI). The proposed scheme adjusts the ts (Kp and Ki) in real time in order to find the most suitable Kp and Ki for PI controller and to simplify the controller design. The proposed scheme is verified the validity by experiment and co-simulation in PSIM and MATLAB/SIMULINK both load step change and input DC voltage variation in Z-source inverter, and has compared with the conventional PID control scheme. The experiment results involve of three-phase output voltage, Z-network capacitor voltage and dc-link peak voltage value. By those analysis and comparison, the availability of the proposed method in output voltage transient response quality improving has been verified. Compared with conventional PID method, the proposed method showed a more effective and robust control performance for coping with the severe disturbance conditions.

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The Parameter Auto-tuning of the Reference Model Following Fuzzy Logic Controller (기준모델 추종 퍼지 제어기의 파라메터 자동 동조)

  • Roh, Chung-Min;Suh, Seung-Hyun;Ko, Bong-Woon;Nam, Moon-Hyon
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1377-1379
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    • 1996
  • In this paper, each parameter was identified by the gradient descent method to overcome difficulty deciding fuzzy rules of FLC for the unknown process and the type of membership Junctions. Usually PID or optimal control theories have been mostly usee in control field so far. However, optimal control requires much time for calculation because of adaptation for disturbance and nonlinearity. And intricate technique such as MRAS which can be realized only by an expert are limited to be used in the systems requiring rapid and precise response because of comparatively longer calculating time and complicateness. Gradient descent method is a method to find Z minimizing a function about a certain vector Z. And required output of FLC is gained using gradient approaching method in order to adapt control rule parameters of FLC. Simulation proved validation of this algorithm.

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