• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.279-281
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• 2006

In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.6
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• pp.30-39
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• 2014

Through a lot of papers, it has been concluded that fuzzy logic controller is superior to PI controller in motor speed control. Although fuzzy logic controller is superior to PI controller in motor speed control, the gain tuning of fuzzy logic controller is more complicated than that of PI controller. In this paper, using mathematical analysis of the PI and fuzzy controller, the design method of the fuzzy controller that has the same characteristics with the PI controller is proposed. After that, we can design the fuzzy controller that has superior performance than PI controller by changing the envelope of input of fuzzy controller to nonlinear, because the fuzzy controller has more degree of freedom to select the control gain than PI controller. The advantage of fuzzy logic controller is shown through mathematical analysis, and the simulation result using Matlab simulink has been proposed to show the effectiveness of these analysis.

• Journal of Drive and Control
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• v.15 no.1
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• pp.28-37
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• 2018

When the wind speed rises above the rated wind speed, the produced power of the wind turbines exceeds the rated power. Even more, the excessive power results in the undesirable mechanical load and fatigue. A solution to this problem is pitch control of the wind turbines. This paper presents a systematic design method of a collective pitch controller for the wind turbines using a discrete fuzzy Proportional-Integral (PI) controller. Unlike conventional PI controllers, the fuzzy PI controller has variable gains according to its input variables. Generally, tuning the parameters of fuzzy PI controller is complex due to the presence of too many parameters strongly coupled. In this paper, a systematic method for the fuzzy PI controller is presented. First, we show the fact that the fuzzy PI controller is a superset of the PI controller in the discrete-time domain and the initial parameters of the fuzzy PI controller is selected by using this relationship. Second, for simplicity of the design, we use only four rules to construct nonlinear fuzzy control surface. The tuning parameters of the proposed fuzzy PI controller are also obtained by the aforementioned relationship between the PI controller and the fuzzy PI controller. As a result, unlike the PI controller, the proposed fuzzy PI controller has variable gains which allow the pitch control system to operate in broader operating regions. The effectiveness of the proposed controller is verified with computer simulations using FAST, a NREL's primary computer-aided engineering tool for horizontal axis wind turbines.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1978-1983
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• 2011

BLDC motor is used in a wide variety of industrial and servo applications. Its features and advantages mainly consist in high value of torque/inertia ratio, high efficiency with speed range and high dynamic performance. This paper deals with the speed control of a trapezoidal type brushless DC motor using Fuzzy PI controller. The conventional PI controller has been widely used in industrial applications. If we select a optimal PI control gain, the PI controller shows very good control performance. But it is very difficult to find the optimal PI control gain. Fuzzy control does not need any model of plant and is basically adaptive and gives robust performance for plant parameter variation. Therefore the combinations of conventional PI controller and fuzzy controller seem to be very effective. This paper deals with PI controller with 4-rule based fuzzy controller. The proposed fuzzy PI controller increases the control performance of the conventional PI controller. Simulation and experimental results show that fuzzy PI controller has a good robustness regarding the improper tuned PI controller.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.12
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• pp.87-97
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• 1993

To improve the limitation of fuzzy PI controller when is applied to systems of order higher than one, a fuzzy PI controller that fuzzily resets or amplifies the accumulated control input according to fuzzy rules defined on (error, change of error) space is proposed. The proposed controller structure was motivated by the characteristics of fuzzy PI controller that it generally gives unevitable large overshoot in trial of reducing rise time of response especially when a system of order higher than one is considered. Based on the observation that the undesirable characteristics of the fuzzy PI controller is caused by integrating control input excessively, even though the integrator is introduced to overcome steady state error, we propose a controller that clear out or doubles integrated control input in a fuzzy manner according to the situation to reduce rise time as well as overshoot. To show the usefulness of the proposed controller, it is applied to the systems that are difficult to stabilize or difficult to get satisfactory response by conventional fuzzy PI controllers.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.221-226
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• 2006

In this paper, we study an approach to design a Fuzzy PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of traditional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. In order to solve the above problems, we adapt Fuzzy PI controller for the fire angle control of rectifier. The performance of the Fuzzy PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain factors of the Fuzzy PI controller by Genetic Algorithms. A comparative study has been performed between Fuzzy PI controller and traditional PI controller, to prove the superiority of the proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.5
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• pp.109-119
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• 1993

To improve limitations of fuzzy PI controllers especially when applied to systems of order higher than one, we propose a fuzzy PI controller that takes out appropriate amounts of accumulated control input according to fuzzily described situations in addition to the calculation of incremental control input as in the case of conventional fuzzy PI controllers. The structure of the proposed controller was motivated by the characteristics of fuzzy PI controller that it generally gives inevitable overshoot when one tries to reduce rise time of the response especially when a system of order higher than one is under consideration. Since the undesirable characteristics of the fuzzy PI controller is caused by integrator of the controller, even though the integrator is introduced to overcome steady state error of response, we propose a controller that fuzzily clears out integrated quantities according to situation to give reduced rise time as well as small overshoots. To show the usefulness of the proposed controller, it is applied in simulations to such systems as are difficult to stabilize or difficult to get satisfactory responses by conventional fuzzy PI controllers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.713-716
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• 2007

In this paper, we consider one of robust control system, fuzzy PI+fuzzy D controller dealing with noise, load, changed parameters of plant. We apply PI+D controller with a design for output of differential function and, we plan fuzzy controller with input for PID parameter of PI+D controller so We design control system meet with the change of environment with robust in relation to change of parameter. Fuzzy control is possessed of easy 4 rules and membership function and We design fuzzy PI+fuzzy D controller. Plant of this paper make a choice of 3 phase induction motor.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1009-1010
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• 2007

This paper presents Fuzzy-Neuro PI controller of IPMSM drive using fuzzy and neural-network. In general, PI controller in computer numerically controlled machine process fixed gain. To increase the robustness, fixed gain PI controller, Fuzzy-Neuro PI controller proposes a new method based fuzzy and neural-network. Fuzzy-Neuro PI controller is developed to minimize overshoot and settling time following sudden parameter changes such as speed, load torque, inertia, rotor resistance and self inductance. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.6
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• pp.1176-1181
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• 2007

In this paper, we consider one of robust control system, fuzzy PI+fuzzy D controller dealing with noise, load, changed parameters of plant. We apply PI+D controller with a design for output of differential function and, we plan fuzzy controller with input for PID parameter of PI+D controller so We design control system meet with the change of environment with robust in relation to change of parameter. Fuzzy control is possessed of easy 4 rules and membership function and We design fuzzy PI+fuzzy D controller. Plant of this paper make a choice of 3 phase induction motor.