• Title/Summary/Keyword: Tuning time

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Development of a reduced-order distillation model and real-time tuning using the extended kalmen filter (증류공정 차수감소 모델의 개발 extended kalmen filter에 의한 실시간대에서의 조정)

  • 정재익;최상열;이광순
    • 제어로봇시스템학회:학술대회논문집
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    • 1988.10a
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    • pp.466-470
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    • 1988
  • A tunable reduced-order distillation model is proposed for real-time applications. To develop the model, a binary distillation column with MaCabe-Thiele assumptions was considered first and then the governing equations for the column were reduced to a simplified vector differential equations using the collocation method combined with cubic spline interpolation function. The final reduced-order model has four tuning parameters, relative volatilities and liquid holdups for rectifying and stripping sections, respectively. To assess the applicability of the developed model,the real-time adjustment of the model was tried by recursively updating the tuning parameters using the BKF algorithm. As a result, it was found that the reduced-model follows the simulated distillation process very closely as the parameters are improved.

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A Tuning Algorithm for LQ-PID Controllers using the Combined Time - and Frequency-Domain Control Method

  • Kim, Chang-Hyun;Lee, Ju;Lee, Hyung-Woo
    • Journal of Electrical Engineering and Technology
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    • v.10 no.3
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    • pp.1244-1254
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    • 2015
  • This paper proposes a new method for tuning a linear quadratic - proportional integral derivative controller for second order systems to simultaneously meet the time and frequency domain design specifications. The suitable loop-shape of the controlled system and the desired step response are considered as specifications in the time and frequency domains, respectively. The weighting factors, Q and R of the LQ controller are determined by the algebraic Riccati equation with respect to the limiting behavior and target function matching. Numerical examples show the effectiveness of the proposed LQ-PID tuning method

An Optimal Tuning of PI-PD Controller Via LQR (LQR을 사용한 최적 PI-PD제어기 동조)

  • Kang, Keun-Hyoung;Suh, Byung-Suhl
    • Proceedings of the KIEE Conference
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    • 2005.05a
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    • pp.109-112
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    • 2005
  • This paper presents an optimal and robust PI-PD controller design method for the second-order systems both with dead time and without dead time to satisfy the design specifications in the time domain via LQR design technique. The optimal tuning method of PI-PD controller are also developed by setpoint weighting and neural networks. It is shown that the simulation results show significantly improved performance by proposed method.

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Design of self-tuning controller utilizing neural network (신경회로망기법을 이용한 자기동조제어기 설계)

  • 구영모;이윤섭;김대종;임은빈;우광방
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.399-401
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    • 1989
  • Utilizing an interconnected set of neuron-like elements, the present study is to provide a method of parameter estimation for a second order linear time invariant system of self-tuning controller. The result from the proposed method is evaluated by comparing with those obtained by the recursive least square (RLS) identification algorithm and extended recursive least square (ERLS) algorithm, and it shows that, although the smoothness of system performance is still to be improved, the effectiveness of shorter computing time is demonstrated which may be of considerable value to real time computing.

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Optimal Tuning of a Ballscrew Driven Biaxial Servo System (외란관측기를 이용한 볼스크류 구동 2축 서보계의 최적튜닝)

  • Shin, Dong-Soo;Chung, Sung-Chong
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.20 no.5
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    • pp.589-597
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    • 2011
  • In this paper, optimal tuning of a cross-coupled controller linked with the feedforward controller and the disturbance observer is studied to improve contouring and tracking accuracy as well as robustness against disturbance. Previously developed integrated design and optimal tuning methods are applied for developing the robust tuning method. Strict mathematical modeling of the multivariable system is formulated as a state-space equation. Identification processes of the servomechanism are conducted for mechanical servo models. An optimal tuning problem to minimize both the contour error and settling time is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servo control system. Constraints such as relative stability, robust stability and overshoot, etc. are considered for the optimization. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm the control performance and robustness despite the variation of parameters of the mechanical subsystems.

Development of Experimental Gain Tuning Technique for Multi-Axis Servo System (다축 서보 시스템의 Gain Tuning에 관한 연구)

  • Chung W.J.;Kim H.G.;Seo Y.G.;Lee K.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2006.05a
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    • pp.271-272
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    • 2006
  • This paper presented a new experimental gain tuning technique for a Multi-Axis Servo System. First, the investigation for proportional gain of velocity control loop by using a Dynamic Signal Analyzer (DSA) was performed. Using the FUNCTION characteristic of DSA based on the Bode plot, the Bode plot of open loop transfer function was obtained. In turn, the integral gain of a servo controller can be found out by using the Integration time constant extracted from the Bode plot of open loop transfer function. In the meanwhile, the positional gain of the servo controller has been obtained by using the Bode plot of the closed loop transfer function. We have also proposed the technique to find out an optimal parameter of a notch filter, which has a great influence on vibration reduction, by using the damping factor extracted from the Bode plot of closed loop transfer function.

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A Design Weighting Polynomial Parameter Tuning of a Self Tuning Controller (자기동조 제어기의 설계 하중다항식 계수 조정)

  • 조원철;김병문
    • Journal of the Korean Institute of Telematics and Electronics T
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    • v.35T no.3
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    • pp.87-95
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    • 1998
  • This paper presents the method for the automatic tuning of a design weighting polynomial parameter of a generalized minimum-variance stochastic self tuning controller which adapts to changes in the system parameters with time delays and noises. The 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 weighting polynomial parameters. The proposed self tuning method is simple and effective compared with other existing self tuning methods. The computer simulation results are presented to illustrate the procedure and to show the performance of the control system.

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Position Control of Shape Memory Alloy Actuators Using Self Tuning Fuzzy PID Controller

  • Ahn Kyoung-Kwan;Nguyen Bao Kha
    • International Journal of Control, Automation, and Systems
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    • v.4 no.6
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    • pp.756-762
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    • 2006
  • Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

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

  • 권오국;주영훈;박진배
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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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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Tuning of Dual-input PSS and Its Application to 612 MVA Thermal Plant: Part 1-Tuning Methology of IEEE Type PSS2A Model (다중입력 PSS 튜닝 방법과 612 MVA 화력기 적용: Part 1-IEEE PSS2A 튜닝 방법)

  • Kim, Dong-Joon;Moon, Young-Hwan;Kim, Sung-Min;Kim, Jin-Yi;Hwang, Bong-Hwan;Cho, Jong-Man
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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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.