• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.31-41
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• 1993

In this paper, a fuzzy adaptive controller is proposed for the process with large delay time and unmodelled dynamics. The fuzzy adaptive controller consists of self tuning controller and fuzzy tuning part. The self tuning controller is designed with the continuous time GMV (generalized minimum variance) using emulator and weighted least square method. It is realized by the hybrid method. The controller has robust characteristics by adapting the inference rule in design parameters. The inference processing is tuned according to the operating point of the process having the nonlinear characteristics considering the practical application. We review the characteristics of the fuzzy adaptive controller through the simulation. The controller is applied to practical electric furnace. As a result, the fuzzy adaptive controller shows the better characteristics than the simple numeric self tuning controller and the PI controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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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.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.48.5-48
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• 2002

$\textbullet$ Contents 1 Introduction $\textbullet$ Contents 2 Crane Description $\textbullet$ Contents 3 Self-tuning Controller Design $\textbullet$ Contents 4 Result of Experiments $\textbullet$ Contents 5 Conclusions $\textbullet$ Contents 6 References

• Proceedings of the KIEE Conference
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• 1987.11a
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• pp.76-78
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• 1987

This paper describes the theory and application of a multi-input/multi-output self-tuning regulator where the control objective is the assignment of the closed-loop pole set to prespecified locations. The algorithm described In this paper has a 'self-tuning' property. This self-tuners are more robust than the tuners that are based on optimal control synthesis method. This paper demonstrate usefulness of the algorithms by means of some simulation studies.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.63-66
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• 1997

The rule bases self organizing controller(SOC) has one of its main advantages in the fact that there is no need to have a mathematical description of the system to be controlled. In this controller, the rules are linguistics statements expressed mathematically through the concepts of fuzzy sets and correspond to the actions a human operator would take when controlling a given process. With this controller, we have performed to sight stabilization system, and we realize that it needs a scale factor tuning. The self tuning controller(STC) uses an instantaneous system fuzzy performance which can give an inspection to the scale factor. Therefore, the STC can compensate the scale factor when it is not adequately tuned. With this trial, we shows that STC can give a good transient characteristics in the nonlinearity which imposed basically in the conventional servo system.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.2
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• pp.60-67
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for a synchronous generator excitation and SVC system. A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the most flexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage. The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly. Using input-output data pair obtained from PSS, the parameters in antecedent part and in consequent part of fuzzy inference rules are learned and tuned automatically using the proposed steepest decent method. The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1251-1258
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• 1999

The water level control of a steam generator in the unclear power plant is an important process. Most of the water level controllers of the actual plant are PID controllers. But they have limitations in appling for tracking the set point and getting rid of disturbances, so there are some defects to apply in the actual ground even though many research works represented the resolutions to solve it. In this paper, it is suggested that the established simple PID controller in low power has the ability to remove disturbances and trace the set-point, and then possesses the real-time self-tuning function according to the variety of moving peculiarity of a plant. This function realized by making use of fuzzy logic. PID parameters are formulated by a variable ${\alpha}$ and made it fluctuate by a fuzzy inference according to level error and level error change. This mechanism makes application of actual plant effective as well as taking advantage of improving the efficiency of water level controller by way of adding the function of self-tuning instead of replacing PID controller. The computer simulation of this scheme shows the improved performance compare to conventional PID controller.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.3
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• pp.199-207
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• 2002

In this paper, a self-tuning gain-scheduled skyhook control for semi-active suspension systems is investigated. The dynamic characteristics of a continuously variable damper including electro-hydraulic pressure control valves is analyzed. A 2-d.o.f. time-varying quarter-car model that permits variations in sprung mass and suspension spring coefficient is considered. The self-tuning skyhook control algorithm proposed in this paper requires only the measurement of body acceleration. The absolute velocity of the sprung mass and the relative velocity of the suspension deflection are estimated by using integral filters. The skyhook gains are gain-scheduled in such a way that the body acceleration and the dynamic tire force are optimized. An ECU prototype is discussed. Experimental results using a 1/4-ear simulator are discussed. Also, a suspension ECU prototype targeting real implementation is provided.

• Journal of Mechanical Science and Technology
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• v.18 no.3
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• pp.379-387
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• 2004

A novel flatness sensing system which is called the Flatness Sensing Inter-stand Looper(FlatSIL) system is suggested and a self-tuning PI control system using the FlatSIL is designed for improving the flatness of hot strip in finishing mill processes. The FlatSIL system measures the tension along the direction of the strip width by using segmented rolls, and the tension profile is approximated through the tension of each segmented roll. The flatness control system is operated by using the tension profile. The proposed flatness control system as far as the tension profile-measuring device works for the full strip length during the strip rolling in finishing mills. The generalized minimum variance self-tuning (GMV S-T) PI control method is applied to control the flatness of hot strip which has a design parameter as weighting factor for updating the PI gains. Optimizing the design parameter in the GMV S-T PI controller, the Robbins-Monro algorithm is used. It is shown by the computer simulation and experiment that the proposed GMV S-T PI flatness control system has better performance than the fixed PI flatness control system.