• 제목/요약/키워드: Parameter Tuning Method

검색결과 282건 처리시간 0.034초

최소분산 자기동조 PID제어기 (A self tuning PID controller with minimum variance)

  • 조원철;전기준
    • 제어로봇시스템학회논문지
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    • 제2권1호
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    • pp.14-20
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    • 1996
  • This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

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Fuzzy 자동동조에 의한 불확실성 공정의 견실제어 (Robust Control of Uncertainty Systems by Fuzzy Auto-Tuning)

  • 류영국;최정내;김진권;모영승;황형수
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.504-506
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    • 1999
  • In this paper, we propose a method which control parametric uncertainty systems using PID controller by fuzzy auto tuning. We get the error and the error change rate of plant output correspond to the initial value of parameter using the Ziegler-Nickols tuning and determine the new proportional gain$(K_p)$ and the integral time $(T_i)$ from fuzzy tuner by the error and error change rate of plant output as a membership function of fuzzy theory. The Fuzzy Auto-tuning algorithm for PID controller operate to adapt variable parameter of plant in parametric uncertainty systems. It is shown this method considerably improve the transient response at computer simulation.

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초기과도 상태를 개선한 자기 동조 제어 방식 (Self-tuning control with improved transient state)

  • 김운성;배한경;허경무
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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    • pp.376-381
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    • 1992
  • In this thesis, a self-tuning control method based on Variable Structure System technique for tracking control of Direct-Drive motor is presented. The self-tuning control could not make the tracking error zero in the transient period. This tracking error may be due to disturbances or the error in parameter identification. To overcome this problem, a self-tuning control method based on discrete time VSS technique is presented. The STC based on VSS technique gives good tracking performance of the reference signal in the transient period. The proposed controller is robust to parameter errors and disturbances. The performance of the proposed controller is compared with that of simple STC through digital computer simulation.

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위상 조절 인자를 고려한 IMC-PID 제어기의 설계 (The Design of IMC-PID Controller Considering a Phase Scaling Factor)

  • 김창현;임동균
    • 전기학회논문지
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    • 제57권9호
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    • pp.1618-1623
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    • 2008
  • In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain and phase margins, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

강인 PID 제어기 설계 (A tuning method for robust PID controller)

  • 윤상준;이상정
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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    • pp.585-588
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    • 1996
  • The conventional output feedback robust control designs are very useful for systems under parameter perturbation and uncertain disturbance. However these designs are very complicated and not easily implemented for industrial applications. So, this paper proposes a robust PID controller design method via genetic searching algorithm.

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신경회로망 기법을 이용한 극-영점 배치 자기 동조 제어기 (Pole-Zero Assignment Self-Tuning Controller Using Neural Network)

  • 구영모;이윤섭;장석호;우광방
    • 대한전기학회논문지
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    • 제40권2호
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    • pp.183-191
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    • 1991
  • This paper develops a pole-zero assignment self-tuning regulator utilizing the method of a neural network in the plant parameter estimation. An approach to parameter estimation of the plant with a Hopfield neural network model is proposed, and the control characteristics of the plant are evaluated by means of a simulation for a second-order linear time invariant plant. The results obtained with those of Exponentially Weighted Recursive Least Squares(EWRLS) method are also shown.

다중입력 PSS 튜닝 방법과 612 MVA 화력기 적용: Part 1-IEEE PSS2A 튜닝 방법 (Tuning of Dual-input PSS and Its Application to 612 MVA Thermal Plant: Part 1-Tuning Methology of IEEE Type PSS2A Model)

  • 김동준;문영환;김성민;김진이;황봉환;조종만
    • 전기학회논문지
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    • 제58권4호
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    • pp.655-664
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    • 2009
  • This paper, Part 1, describes the effective dual-input PSS parameter design procedure for the IEEE Type PSS2A against the Dangjin 612 MVA thermal plant's EX2000 excitation system. The suggested tuning technique used the model-based PSS tuning method and consisted of three steps: 1) generation system modeling; 2) determination of PSS2A model parameters using linear, time-domain transient and 3-phase simultaneous analyses, and 3) field testing and verification, which are described in Part 2. The effective PSS2A model parameters of EX2000 system in the Dangjin T/P #4 were designed according to the suggested procedure, and verified by using three analyses.

Hyper Parameter Tuning Method based on Sampling for Optimal LSTM Model

  • Kim, Hyemee;Jeong, Ryeji;Bae, Hyerim
    • 한국컴퓨터정보학회논문지
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    • 제24권1호
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    • pp.137-143
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    • 2019
  • As the performance of computers increases, the use of deep learning, which has faced technical limitations in the past, is becoming more diverse. In many fields, deep learning has contributed to the creation of added value and used on the bases of more data as the application become more divers. The process for obtaining a better performance model will require a longer time than before, and therefore it will be necessary to find an optimal model that shows the best performance more quickly. In the artificial neural network modeling a tuning process that changes various elements of the neural network model is used to improve the model performance. Except Gride Search and Manual Search, which are widely used as tuning methods, most methodologies have been developed focusing on heuristic algorithms. The heuristic algorithm can get the results in a short time, but the results are likely to be the local optimal solution. Obtaining a global optimal solution eliminates the possibility of a local optimal solution. Although the Brute Force Method is commonly used to find the global optimal solution, it is not applicable because of an infinite number of hyper parameter combinations. In this paper, we use a statistical technique to reduce the number of possible cases, so that we can find the global optimal solution.

Hyundai 8608 Robot 제어기 파라미터 튜닝 방안 연구 (A Study on the Control Parameter Tuning Method of the Hyundai 8608 Robot)

  • 김미경;윤천석;강희준;서영수;노영식;손홍래
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2005년도 춘계학술대회 논문집
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    • pp.1836-1840
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    • 2005
  • This work proposes a controller tuning method of a Hyundai 8608 robot in order to improve its performance. For this, we analyzed the control structure of the robot, and the functions of all the adjustable parameters in the robot controller with a reference 'NACHI Technical Report'. Through the analysis, we found out that 3 important parameters(VRRL, VRF, VRGIN) act like a conventional PID gains and other parameters are closely related to these 3 parameters. Conclusively, parameter tuning of these 3 parameters is enough in most cases of applications with other parameters fixed. The conventional PID tuning is performed to each joint of the test robot with Robot Performance Evaluation System(shown in our companion paper) so that the acceptable gain ranges for each joint are determined and then the robot performance tests are repeatedly done with the combination of the acceptable gains. Finally, the best combination is selected for its best performance. For the effectiveness of the proposed method, it was implemented on a Hyundai 8608 robot and its results are compared with the results of NACHI's Semi-Auto Tuning Method and the results which are done by a tuning expert with his eyes.

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

  • 이은철;김종훈;이인희;남문현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1995년도 하계학술대회 논문집 B
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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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