• International Journal of Aeronautical and Space Sciences
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• v.3 no.1
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• pp.86-94
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• 2002

The initial alignment of inertial platform for navigation system was considered. An adaptive filtering technique is developed for the system with unknown and varying sway disturbance. It is assumed that the random sway motion is the second order ARMA(Auto Regressive Moving Average) model and performed parameter identification for unknown parameters. Designed adaptive filter contain both a Kalman filter and a self-tuning filter. This filtering system can automatically adapt to varying environmental conditions. To verify the robustness of the filtering system, the computer simulation was performed with unknown and varying sway disturbance.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.109-112
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-control In various fields. First of all, in this method, 1st order delay system with dead time which is modelled from the unit step response of the system is Pade -approximated, then initial values are determined by the Ziegler-Nichols method. After inputting constraints of evolution programs, we perform crossover and mutation to generate the descendant generation. The advantage of this method is better than the Ziegler-Nickels method in characteristic of output and has extent of applying without limit of K, L, T.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3038-3047
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• 1996

In telerobot systems, visual servoing of a task object for a slave arm with an eye-in-hand has drawn an interesting attention. As such a task ingenerally conducted in an unstructured environment, it is very difficult to define the inverse feature Jacobian matrix. To overcome this difficulty, this paper proposes an auto-tuning fuzzy rule-based visual servo algorithm. In this algorithm, a visual servo controller composed of fuzzy rules, receives feature errors as inputs and generates the change of have position as outputs. The fuzzy rules are tuned by using steepest gradient method of the cost function, which is defined as a quadratic function of feature errors. Since the fuzzy rules are tuned automatically, this method can be applied to the visual servoing of a slave arm in real time. The effctiveness of the proposed algorithm is verified through a series of simulations and experiments. The results show that through the learning procedure, the slave arm and track object in real time with reasonable accuracy.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.7 no.4
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• pp.42-50
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• 1993

This paper was proposed drive strategy Induction Motor using the fuzzy algorithm of auto-tuning PID control. In fuzzy control, the 1M driving system is controlled in trial and error without the mathematical modeling and using fuzzy lookup table the real time control is possible. Also, ,dividing the fuzzy rules in several zone, the stability and response of the 1M driving system is improved. The parameters of 1M are varying according to the environmental conditions, the variance of the parameters is affected with the driving characteristics of 1M. Using the fuzzy algorithm of the driving system which has the auto tuning control function for high performance, high accuracy of the driving system, a designed and proposed through the comparision with the PID control method and the driving characteristics is reviewed and analyzed.

• Proceedings of the KWS Conference
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• 1999.05a
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• pp.207-210
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• 1999

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.51-56
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• 1998

In this paper, we analyze the effects of scaling factors on the performance of a fuzzy logic controller(FLC). The quantitative relation between input and output variables of FLC is obtained by using a qualsi-linear fuzzy model, and an approximate transfer function of FLC is dervied from the comparison of it with the conventional PID controller. Then we analyze in detail the effects of scaling factor using this approximate transfer function and root locus method. Also we suggest an on-line tuning method for scaling factors which employs an sample performance function and a variable reference for tuning index.

• Journal of KSNVE
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• v.8 no.3
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• pp.441-449
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• 1998

A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2651-2654
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• 2000

In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a self tuning fuzzy PID controller whose input output scaling factors were tuned automatically. At first stage, the tuning parameters of fuzzy controller were determined by Ziegler-Nichols tuning method and then they were adjusted as the delay time and process environment were changed. Proposed controller was simple in its structrue and computational burden was small so that on line adaptation was easy to apply to. The result of computer simulation and practical experiment showed the proposed controller's excellent performance

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.436-438
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• 1993

A rule based fuzzy expert system in self-tune PID controllers is presented in this paper. The rule base. the core of the expert system, is extracted from the Wills' tuning map and the author's knowledge about the implicit relations between PID gains and controlled output response. The overall control system consists of the relay feedback scheme and the expert system, where the one is responsible for initial tuning and the other for subsequent tuning. The PID control system with the proposed fuzzy expert system, shows better convergence rate and control performances than those of a Litt in spite of the fact that the two rule bases are extracted from the same maps provided by Wills.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.604-610
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• 2007

Injection molding is the most common method of shaping plastic resins for manufacturing a variety of parts. This injection molding is accomplished by injection molding machines (IMM) which consists of a hewer, a reciprocating screw, barrel assembly, and an injection nozzle. The plastic resin is fed to the machine through the hopper and it should be heated to the target melting temperature, which depends on material properties, as closely as possible with very small temperature overshoot in the barrel. Since the barrel, which has temperature dependent specific heat and thermal conductivity in the operating temperature range, is heated by the several electric heater bands, it is not an easy task to control the temperature of the barrel owing to the interference of neighboring heaters and its material properties. Though PID controller with auto-tuning capability is widely adopted in the nm, the auto-tuning process should be carried out whenever the operating temperature is changed significantly. Recently, though the predictive controller is developed and shows good performance, it has drawbacks: 1. Since the heat transfer modeling process is very complicated and should be carried out again when the barrel is changed, it is somewhat inappropriate in the field. 2. The controller performance is not validated in whole operating temperature range. In this paper, cascade type simple PI controller with input restriction is proposed to find the possibility of controlling the barrel temperature in the whole operating temperature range. It is shown by experiment that the proposed controller shows good performance. This result can be applied to design of PI controller with auto-tuning capability.