• 제목/요약/키워드: Effectiveness Tuning Method

검색결과 143건 처리시간 0.026초

Ziegler-Nichols 방법을 이용한 이산형 PID제어기의 자동동조 (On the Auto-Tuning of a Discrete PID Controller Based on the Ziegler and Nichols's Method)

  • 이영일;권욱현
    • 대한전기학회논문지
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    • 제40권8호
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    • pp.774-781
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    • 1991
  • This paper proposes an auto-tuning method of a discrete -PIC controllers which is based on the Ziegler and Nichols's PID Tuning Rule. This tunign rule is derived using the Pade's first order approximation and it prevents the performance degradation caused by the time-delay effect of zero order holder when the Ziegler-Nichols tuning rule is applied to a discrete PID controller. A simple and practical auto-tuning method is proposed through combining this discrete tuning rule with the relay control. The auto-tuning scheme is implemented on a microprocessor based system and is applied to a position control system to show the effectiveness of the discrete tuning rule.

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초타원 가우시안 소속함수를 사용한 퍼지신경망 모델링 (Fuzzy neural network modeling using hyper elliptic gaussian membership functions)

  • 권오국;주영훈;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.442-445
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    • 1997
  • We present a hybrid self-tuning method of fuzzy inference systems with hyper elliptic Gaussian membership functions using genetic algorithm(GA) and back-propagation algorithm. The proposed self-tuning method has two phases : one is the coarse tuning process based on GA and the other is the fine tuning process based on back-propagation. But the parameters which is obtained by a GA are near optimal solutions. In order to solve the problem in GA applications, it uses a back-propagation algorithm, which is one of learning algorithms in neural networks, to finely tune the parameters obtained by a GA. We provide Box-Jenkins time series to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

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GPC기법을 이용한 자기동조 PID제어기 설계 (Design of Self-Tuning PID Controller Using GPC Method)

  • 윤강섭;이만형
    • 한국정밀공학회지
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    • 제13권5호
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    • pp.139-147
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    • 1996
  • PID control has been widely used for real control systems. Particularly, there are many researches on control schemes of tuning PID gains. However, to the best of our knowledge, there is no result for discrete-time systems with unknown time-delay and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown papameters and unknown time-delay system. A numerical simulation was presented to illustrate the effectiveness of this method.

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A Systematic Gain Tuning of PID Controller Based on the Concept of Time Delay Control

  • Lee, Jeong-Wan
    • International Journal of Precision Engineering and Manufacturing
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    • 제9권4호
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    • pp.39-44
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    • 2008
  • In this paper, through the study of discrete implementation of time delay control (TDC) and PID control algorithm, a new systematic gain selection method for PID controller is proposed. An important advantage of this method is that it may be applied to real systems with very simple and systematic procedure. The proposed method is derived for SISO systems and then extended to MIMO system. Through simulation for the second order non-linear plant and experiment on 2-DOF robot, the effectiveness of the proposed method is confirmed. The proposed method could solve the problem of difficulty in gain tuning of existing PID controller.

자동 양자이득 조정에 의한 퍼지 제어방식 (Fuzzy Control Method By Automatic Scaling Factor Tuning)

  • 강성호;임중규;엄기환
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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    • pp.2807-2810
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    • 2003
  • In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

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흡기관 복합공진을 위한 기관의 시뮬레이션 연구 (A Study on the Multi-Tuning for Intake Manifold Using Engine Simulation)

  • 이응석
    • 대한기계학회논문집
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    • 제18권12호
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    • pp.3315-3325
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    • 1994
  • To study the variation of charging efficiency in the engine intake, the method to change the natural frequency of intake system using the intake control valve was studied and it has been used in actual engine to increase the intake air. In this paper, the method of characteristics was used to analyze the non-steady state and compared with the experimental data of the 6-cylinder diesel engine showing the effectiveness of the method theoretically.

고정밀 운동제어를 위한 2축 서보메커니즘의 최적튜닝 (Optimal Tuning of Bi-axial Servomechanisms for High-Precision Motion Control)

  • 성철모;정성종
    • 한국공작기계학회논문집
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    • 제17권5호
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    • pp.44-51
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    • 2008
  • In this paper, the optimal tuning of a cross-coupled controller linked with the feedforward controller is studied to reduce contouring and tracking errors of a bi-axial servomechanisms by using the previously developed integrated tuning method. The CCC system for an arbitrary curve, which is combined with the feedforward controller, is formulated by a state-space based on a series of linear motion trajectories. An optimal tuning problem is formulated as a nonlinear constrained optimization problem including relevant controller parameters of the servo. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm that both tracking and contouring errors are significantly reduced by applying the proposed control and tuning system.

센서 잡음 저감도 및 안정-강인성을 고려한 PID-PD 제어기의 최적 동조 (Optimum Tuning of PID-PD Controller considering Robust Stability and Sensor Noise Insensitivity)

  • 김창현;임동균;서병설
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.628-631
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    • 2005
  • In this paper, we propose tuning method of PID-PD controller to satisfy design specifications in frequency domain as well as time domain. The proposed tuning method of PID-PD controller that consist of the convex set of PID and PI-PD controller controls the closed-loop response to locate between the step responses, and Bode magnitudes of closed-loop transfer functions controlled by PID and PI-PD controller. The controller is designed by the optimum tuning method to minimize the proposed specific cost function subject to sensor noise insensitivity and robust stability. Its effectiveness is examined by the case study and analysis.

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GPC 기법을 이용한 자기동조 PID 제어기 설계

  • 윤강섭;이만형
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 1995년도 춘계학술대회 논문집
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    • pp.326-329
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    • 1995
  • PID control has been widely used for real control system Further, there are muchreasearches on control schemes of tuning PID gains. However, there is no results for discrete-time systems with unknown time-dealy and unknown system parameters. On the other hand, Generalized predictive control has been reported as a useful self-tuning control technique for systems with unknown time-delay. So, in this study, based on minimization of a GPC criterion, we present a self-tuning PID control algorithm for unknown parameters and unknown tiem-delay system. A numerical simulation was presented to illuatrate the effectiveness of this method.

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초타원 가우시안 소속함수를 사용한 퍼지 추론 시스템의 하이브리드 자기 동조 기법 (Hybrid Self-Tuning Method for the Fuzzy Inference System Using Hyper Elliptic Gaussian Membership Function)

  • 권오국;장욱;주영훈;박진배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1997년도 하계학술대회 논문집 B
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    • pp.379-382
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    • 1997
  • We present a hybrid self-tuning method using hyper elliptic Gaussian membership function. The proposed method applies a GA to identify the structure and the parameters of a fuzzy inference system. The parameters obtained by a GA, however, are near optimal solutions. So we solve this problem through a backpropagation-type gradient method. It is called GA hybrid self-tuning method in this paper. We provide a numerical example to evaluate the advantage and effectiveness of the proposed approach and compare with the conventional method.

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