• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.663-668
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• 1990

This paper deals with the application of a Generalized Predictive Control (CPC) to a Pressurized Water Reactor (P.W.R) Nuclear Power Plant. Generalized Predictive Control is a sort of Explicit Self-Tuning Control. Current self-tuning algorithms lack robustness to prior choices of either dead-time (input time delay of a plant) or model order. GPC is shown by simulation studies to be superior to accepted self-tuning techniques such as minimum variance and pole-placement from the viewpoint that it is robust to prior choices of dead-time or model order. In this paper a GPC controller is designed to control the P.W.R. nuclear power rlant with varying dead-time and through the designing procedure the designer is free from the constraint of knowing the exact dead-time. The controller is constructed based on the 2nd order linear model approximated in the vicinity of operating point. To ensure that this low-order model describes the complex real dynamics well enough for control purposes, model parameters are updated on-line with a Recursive Least Squares algorithm. Simulation results are successful and show the possibilities of the GPC control application to actual plants with varying or unknown dead-time.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.160-166
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• 2005

In this paper, to overcome drawbacks of FLC a self tuning fuzzy sliding mode controller is proposed, which controls the position of excavator's attachment, which can be regarded as an ill-defined system. It is reported that fuzzy logic theory is especially useful in the control of ill-defined system. It is important in the design of a FLC to derive control rules in which the system's dynamic characteristics are taken into account. Control rules are usually established using trial and error methods. However, in the case where the dynamic characteristics vary with operating conditions, as in the operation of excavator attachment, it is difficult to find out control rules in which all the working condition parameters are considered. Experiments are carried out on a test bed which is built around a commercial Hyundai HX-60W hydraulic excavator. The experimental results show that both alleviation of chattering and performance are achieved. Fuzzy rules are easily obtained by using the proposed method and good performance in the following the desired trajectory is achieved. In summary, the proposed controller is very effective control method for the position control of the excavator's attachment.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.360-364
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• 1989

In this paper, the robustness of self tuning controller for continuous time system is investigated. The continuous time least square algorithm is used in estimating parameters. The main control algorithm is the pole-zero placement control. The effects of unmodeled dynamics on continuous time approach and discrete-time approach are compared.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.476-481
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• 1988

In this paper a pH process of a weak acid with a strong base is modeled into a bilinear form, and a self-tuning pH control algorithm which is robust against initial values of solution and disturbances is presented. The control algorithm employs the recursive least square method for the parameter estimation and the generalised minimum variance criterion as the objective function. The computer simulation shows that the tracking of desired pH values is obtained in satisfactory manner regardless of the initial values chosen for the process.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.246-249
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• 1988

In this paper, a new design technique which uses weighted least-sqare approach for the solution of the pole assignment problem is represented. This technique maybe used to assign some closed loop poles to places which reduce the large system input and output variance due to near pole-zero condition. The least-square approach is also applied to the design of servo self-tuning controller with integrator.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.90-94
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• 1986

This paper describes expansion of the state space pole assignment self-tuning control of SISO systems with system noise and abservation noise to that of MIMO systems. Resursive Prediction Error method is used for both parameter and state estimation in the block controllable canonical form. This simplifies the state feedback law by eliminating the online computation of transformation matrix.

• Journal of the Korean Institute of Intelligent Systems
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• v.3 no.4
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• pp.24-31
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• 1993

원전 증기발생기의 수위제어기를 퍼지제어기로 구성하는 경우 증기발생기의 단독운전이 아닌 전체발전소의 가동중에 소속함수 조정이 이루어져야 하는 제약환경을 고려할 때 많은 반복실행횟수를 필요로 하는 임의적인 시행착오방법이나 일반화되어 있지 않은 복잡한 방법보다는 보다 간단명료하고 예측가능한 조정경로를 통해 소속함수를 조정할 필요가 있다. 여기에서는 그 방안으로서 프로세스 제어응답의 최대초과량 상승시간의 합으로 평가함수를 도입하고 descent method를 이용하여 제어응답의 결과로 얻는 평가함수의 최소점을 따라 소속함수를 조정해가는 방법을 제시하였다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.2
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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.

• Proceedings of the KIEE Conference
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• 1986.07a
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• pp.132-135
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• 1986

This paper shows that using the multivariable controller reduces the magnitude of fluctuations of the control signals which result improved control of the steam generator outputs. Comparison of the performance of the multivariable weighted adaptive controller(MWAC) with the performance of the existing PI controller and the self_tuning controller/1/, when the system goes through a transient mode, shows that the out-puts stay closer to their set points when they are controlled by the adaptive controller.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1188-1190
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• 2001

This paper presents a clustering adaptive controller to achieve robustness against parameter variations although it has simple structure and computational simplicity. The presented controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. The controller requires no model of the system to be controlled. Simulation results show that the usefulness of the proposed controller.