• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.819-826
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• 1994

This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy sets. Each fuzzy set is characterized by a membership function. The tuning fuzzy controller has paramenters that are input/output scaling factors to effect control output. In this paper we propose a tuning method for the scaling factor Computer simulations carried out on first-order and second-order processes will show how the present tuning approach improves the transient and the steady-state characteristics of the overall system.The applicability of the proposed algorithm is certified by computer simulation results.

• Proceedings of the IEEK Conference
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• 2003.07c
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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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.11
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• pp.2010-2016
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• 2007

PID control is windely used to control stable processes, However, its application to integrating processes is less common. In this paper, we proposed a stable PID controller tuning method for integrating processes with time delay using model reduction method. For proposed model reduction method, it disconnect an integrating factor from integrating processes and reduces separate process using reduction method. and it connect an integrating factor to reduced model. We can obtain stable integrating processes using P controller in inner feedback loop and PID tuning is then used to cancel the pole of the feedback loop. This guarantees both robustness and performance. Simulation examples are given to show the good performance of the proposed tuning method comparing with other methods.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.218-220
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• 1993

This paper deals with a self-tuning fuzzy controller. The fuzzy controller is constructed with linguistic rules which consist of the fuzzy variables and fuzzy sets. Each of fuzzy sets is characterized by a membership function. The tuning fussy controller has paramemters to effect control output. In this paper we propose tuning method for the scaling factor. Computer simulations carried out on a second-order process will show how the present tuning approach improves the transient and steady-state characteristics of the overall system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.9
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• pp.1618-1623
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• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain and phase margins, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.701-706
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• 1998

A design method of rule -based fuzzy modeling is presented for the model identification of complex and nonlinear systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient form of " IF..., THEN,," statements. using the theories of optimization and linguistic fuzzy implication rules. The improved complex method, which is a powerful auto-tuning algorithm, is used for tuning of parameters of the premise membership functions in consideration of the overall structure of fuzzy rules. The optimized objective function, including the weighting factors, is auto-tuned for better performance of fuzzy model using training data and testing data. According to the adjustment of each weighting factor of training and testing data, we can construct the optimal fuzzy model from the objective function. The least square method is utilized for the identification of optimum consequence parameters. Gas furance and a sewage treatment proce s are used to evaluate the performance of the proposed rule-based fuzzy modeling.

• 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.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.4
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• pp.388-398
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• 1998

In constructing fuzzy control systems. there are many parameters such as rule base. membership functions. inference m method. defuzzification. and I/O scaling factors. To control the system in properly using fuzzy logic. we have to consider t the correlation with those parameters. This paper deals with self-tuning of fuzzy control systems. The fuzzy controller h has parameters that are input and output scaling factors to effect control output. And we propose the looklongleftarrowup table b based self-tuning fuzy controller. We propose the PMTM(Plus-Minus Tuning Method) for self tuning method, self-tuning the initial look-up table to the appropriate table by adding and subtracting the values.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.559-559
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• 2012

We developed a new scheme for the highly sensitive near-field scanning optical microscope (NSOM) by using a dithering sample stage rather than a dithering probe. In the proposed scheme, the sample is directly loaded on one prong surface of a dithering bare tuning fork. Gap control between probe and sample is performed by detecting the shear force between an immobile fiber probe and the dithering sample. In a conventional NSOM, the Q factor drastically decreases from 7783 to 1000 or even to 100 by attaching a probe to the tuning fork. In our proposed NSOM, on the contrary, the Q factor does not change significantly, 7783 to 7480, when the sample is loaded directly to the tuning fork instead of attaching a probe. Consequently, the graphene sheets that cannot be observed by a conventional NSOM were clearly observed by the proposed method with sub-nanometer vertical resolution due to the extremely high Q factor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.213-217
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• 2008

In this paper, a new design method for IMC-PID that adds a phase scaling factor of system identifications to the standard IMC-PID controller as a control parameter is proposed. Based on analytically derived frequency properties such as gain, phase margin and maximum magnitude of sensitivity function, this tuning rule is an optimal control method determining the optimum values of controlling factors to minimize the cost function, integral error criterion of the step response in time domain, in the constraints of design parameters to guarantee qualified frequency design specifications. The proposed controller improves existing single-parameter design methods of IMC-PID in the inflexibility problem to be able to consider various design specifications. Its effectiveness is examined by a simulation example, where a comparison of the performances obtained with the proposed tuning rule and with other common tuning rules is shown.