• 대한전기학회:학술대회논문집
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• 대한전기학회 2002년도 학술대회 논문집 전문대학교육위원
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• pp.60-63
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for SVC system, A SVC constructed by a Fixed Capacitor and a Thyristor Controlled Reactor is designed and implemented to improve the damping 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, The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 B
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• pp.1142-1144
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• 2003

This Paper presents a speed controller based on the adaptive fuzzy tuning method for brushless DC(BLDC) motor drives under load variations. Generally, the speed tracking control systems use PI controller due to its simple structure and easy of design. PI controller, however, suffers from the electrical machine parameter variations and disturbances. In order to improve the tracking control performance under load variations, PI controller of which the parameters are modified during operation by adaptive fuzzy tuning method. This method based on optimal fuzzy logic system has simple structure and computational simplicity. It needs only sample data which is obtained by optimal controller off-line. As the sample data implemented in the adaptive fuzzy system can be modified or extended, a flexible control system can be obtained. Simulation results show the usefulness of the proposed controller.

• 한국정밀공학회지
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• 제12권8호
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• pp.168-175
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• 1995

A robust speed control algorithm under disturbances and reference change is developed using the self tuning control method in order to control induction motors. The method incorporates the concepts of the well known internal model principle and the annihilator polynomial. The effectiveness of the method is evaluated through the speed control experimental results of an induction motor for refernce change and arbitrary distrbance.

• Computers and Concrete
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• 제30권5호
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• pp.357-367
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• 2022

In this paper, we propose an efficient control method that can be transformed into a general building control problem for building structure control using these reliability criteria. To facilitate the calculation of controller H∞, an efficient solution method based on Linear Matrix Inequality (LMI) is introduced, namely H∞-based LMI control. In addition, a self-tuning predictive grey fuzzy controller is proposed to solve the problem caused by wrong parameter selection to eliminates the effect of dynamic coupling between degrees of freedom (DOF) in Self-Tuning Fuzzy Controllers. We prove stability using Lyapunov's stability theorem. To check the applicability of the proposed method, the proposed controller is applied and the control characteristics are determined. The simulation assumes system uncertainty in the controller design and emphasizes the use of acceleration feedback as a practical consideration. Simulation results show that the performance of the proposed controller is impressive, stable, and consistent with the performance of LMI-based methods. Therefore, an effective control method is suitable for seismic reinforcement of civil buildings.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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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 Electrical Engineering and Technology
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• 제3권1호
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• pp.101-107
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• 2008

We introduce an optimization of fuzzy set-fuzzy systems based on IG (Information Granules). The proposed fuzzy model implements system structure and parameter identification by means of IG and GAs. The concept of information granulation was coped with to enhance the abilities of structural optimization of the fuzzy model. Granulation of information realized with C-Means clustering helps determine the initial parameters of the fuzzy model such as the initial apexes of the membership functions in the premise part and the initial values of polynomial functions in the consequence part of the fuzzy rules. The initial parameters are adjusted effectively with the help of the GAs and the standard least square method. To optimally identify the structure and the parameters of the fuzzy model we exploit GAs with successive tuning method to simultaneously search the structure and the parameters within one individual. We also consider the variant generation-based evolution to adjust the rate of identification of the structure and the parameters in successive tuning method. The proposed model is evaluated with the performance of the conventional fuzzy model.

• 로봇학회논문지
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• 제2권1호
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• pp.1-8
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• 2007

This paper presents a PID automatic gain-tuning algorithm for the electronic throttle valve which is driven by wire. Since the system characteristics of position control for electronic throttle valve are so complicated that both the real time robustness and the manufacturing cost must be considered for mass production. To resolve this paradox, a kind of algorithm called RLS (Recursive Least Square) is adopted for the control of the ETB (Electronic Throttle Body). Using this algorithm, the PID gains can be adjusted automatically with the estimated system parameters. Furthermore, a pre-filter is supplemented for the sake of the robustness against the friction and loads. From the industrial requests for the system, the design specifications are decided as follows: the settling time should be less than 1sec and the overshoot should be kept below 3%. The results of the experiments based on this approach show that the high robustness can be achieved while the system stability is satisfied steadily. A parameter estimation scheme and a gain-tuning algorithm have been properly combined and utilized in this research and the effectiveness is verified through the real experiments.

• 전기학회논문지P
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• 제51권2호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2123-2125
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• 2001

In thermal power plant, the efficiency of a combined power plant with a gas turbine increases, exceeding 50%, while the efficiency of traditional steam turbine plants is approximately 35% to 40%. Up to the present time, the PID controller has been used to operate this system. However, it is very difficult to achieve an optimal PID gain without any experience, since the gain of the PID controller has to be manually tuned by trial and error procedures. This paper focuses on the neural network tuning of the 2-DOF PID controller with a separated 2-DOF parameter (NN-Tuning 2-DOF PID controller), for optimal control of the Gun-san gas turbine generating plant in Seoul. Korea. In order to attain optimal control, transfer function and operating data from start-up, running, and stop procedures of the Gun-san gas turbine have been acquired, and a designed controller has been applied to this system. The results of the NN-Tuning 2-DOF PID are compared with the PID controller and the conventional 2-DOF PID controller tuned by the Ziegler-Nichols method through experimentation. The experimental results of the NN-Tuning 2-DOF PID controller represent a more satisfactory response than those of the previously-mentioned two controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1655-1658
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• 1991

This paper considers the design and analysis of one-step ahead optimal and adaptive controllers, under the restriction that a known constraint on the input amplitude is imposed. It is assumed that the discrete-time single-input, single-output system to be controlled is linear, except for inequality constraints on the input. The objective function to be minimized is an one-step quadratic function, where polynomial weights on the input and output are included. Both the known parameter and unknown parameter (indirect adaptive controller) cases are examined.