• 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.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.404-406
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• 1998

In this paper, we propose a scaling factor tuning method to improve the performance of fuzzy controller. Tuning rules and reasoning are utilized on-line to determine the scaling factors based on absolute value of the error and its difference. A adaptive evolutionary computation (AEC) is used to search for the optimal tuning rules that will maximize the fitness function. Finally, the proposed fuzzy controller is applied to the angular stabilization of an inverted pendulum.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.123-128
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• 1992

This paper presents an autotuning algorithm of scaling factor in order to improve system performance. We define the scaling factor of fuzzy controller as a function of error and error change. This function is tuned by the output of performance evaluation level utilizing the error of overshoot and rising time. Simulation results show that the proposed algorithm has good tuning performance for a system with parameter change.

• 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.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.3
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• pp.17-27
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• 1996

More fuzzy hardware are expected to be utilized in the future to construct fuzzy logic controllers (FLCs). It is hard to find an existing fuzzy hardware which is adopting advanced functions such as self-tuning algorithm in addition to the conventional inference calculation. That is mainly because conventional self-tuning algorithms designed to implement with some hardware circuits is required for fuzzy hardwares to have self-tuning capability. As a first step toward the feature, a novel self-tuning algorithm is proposed in this paper. Based on the search method, the main idea of the proposed algorithm is to detemine valid ranges of input variables of an FLC in order to maximize performance indices fo the control system. The performance indices are so ismple as to be realized by hardware circuit. in dadditon to the conventional scaling-factor adjustment, the algorithm adjusts offset values as well, which, in effect, modifies fuzzy rules of the FLC. To justify the performance of the proposed algorithm, a simulation study is executed.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1110-1115
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• 2004

Acoustic behavior in gas turbine combustor with acoustic resonator is investigated numerically by adopting linear acoustic analysis. Helmholtz-type resonator is employed as acoustic resonator to suppress acoustic instability passively. The tuning frequency of acoustic resonator is adjusted by varying its length. Through harmonic analysis, acoustic-pressure responses of chamber to acoustic excitation are obtained and the resonant acoustic modes are identified. Acoustic damping effect of acoustic resonator is quantified by damping factor. As the tuning frequency of acoustic resonator approaches the target frequency of the resonant mode to be suppressed, mode split from the original resonant mode to lower and upper modes appears and thereby complex patterns of acoustic responses show up. Considering mode split and damping effect as a function of tuning frequency, it is desirable to make acoustic resonator tuned to broad-band frequencies near the maximum frequency of those of the possible upper modes.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.897-899
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• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.1 s.232
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• pp.95-102
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• 2005

Acoustic behavior in gas turbine combustor with acoustic resonator is investigated numerically by adopting linear acoustic analysis. Helmholtz-type resonator is employed as acoustic resonator to suppress acoustic instability passively. The tuning frequency of acoustic resonator is adjusted by varying its length. Through harmonic analysis, acoustic-pressure responses of chamber to acoustic excitation are obtained and the resonant acoustic modes are identified. Acoustic damping effect of acoustic resonator is quantified by damping factor. As the tuning frequency of acoustic resonator approaches the target frequency of the resonant mode to be suppressed. mode split from the original resonant mode to lower and upper modes appears and thereby complex patterns of acoustic responses show up. Considering mode split and damping effect as a function of tuning frequency, it is desirable to make acoustic resonator tuned to broad-band frequencies near the maximum frequency of those of the possible upper modes.

• 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.