• Proceedings of the KIPE Conference
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• 2012.11a
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• pp.29-30
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• 2012

This paper describes a fuzzy PI control method to control the output voltage of three-phase Z-source PWM rectifier. The proposed fuzzy PI controller is a single input fuzzy with its fuzzification, inferences and de-fuzzification processes. The proposed method adjusts the Kp and Ki in real time in order to find the most suitable Kp and Ki for PI controller and to simplify the controller design. The PI portion of DC voltage controller is controlled by fuzzy method. The simulation is performed with PSIM and MATLAB/SIMULINK and is verified the validity of the proposed approach.

• Proceedings of the KIPE Conference
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• 2002.11a
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• pp.40-44
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• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.3
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• pp.30-37
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• 2004

This thesis develops a fuzzy-PID control algorithm for control the filament winding tension. It is developed by applying classical PID control technique to a fuzzy logic controller. It is composed of a fuzzy-PI controller and a fuzzy-D controller. The fuzzy-PI controller uses error and integrated error as inputs, and the fuzzy-D controller uses derivative of error as input. The fuzzy-PI controller uses Takagi-Sugeno fuzzy inference system, and the fuzzy-D controller uses Mamdani fuzzy inference system. The fuzzy rule base for the fuzzy-PI controller is designed using 19 rules, and the fuzzy rule base for the fuzzy-D controller is designed using 5 rules. A test-bed is set-up for verifying the effectiveness of the developing control algorithm in control the filament winding tension. It is composed of a mandrel, a carriage, a force sensor, a driving roller, nip rollers, a creel, and a real-time control system. Nip rollers apply a vertical force to a filament, and the driving roller drives it. The real-time control system is developed by using MATLAB/xPC Target. First, experiments for showing the inherent problems of an open-loop control scheme in a filament winding are performed. Then, experiments for showing the robustness of the developing fuzzy-PID control algorithm are performed under various working conditions occurring in a filament winding such as mandrel rotating speed change, carriage traversing, spool radius change, and reference input change.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.411-419
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• 1998

In this paper the steady-state genetic algorithm is applied for the optimal design of fuzzy PID controllers. Basically the structure of the discussed fuzzy PID controller is extended from the conventional fuzzy PI and PD controllers where only a two-dimensional rule base of the fuzzy PID controller are designed simultaneously. Simulations results shows the superior performance of this optimal designed fuzzy PID controllers to the optimal designed conventional fuzzy PI and PD controllers.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.3
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• pp.295-300
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• 2018

Conventionally, a PI control algorithm has been widely used as a speed control algorithm for BLDC motor. The PI control algorithm has a disadvantage in that is slow to reach the steady state due to the slow speed and torque response with various speed changes. Therefore, in this paper, PWM fuzzy logic control algorithm which can reach the steady state quickly by improving the response speed although there is a little overshoot is proposed. PWM reduces response speed and fuzzy logic control algorithm minimizes overshoot. The proposed PWM fuzzy logic control algorithm consists of DC chopper, PWM duty cycle regulator, and fuzzy logic controller. The performance and validity of the proposed algorithm is verified by simulation with Simulink of Matlab 2018a.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2012-2014
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• 1998

The conventional PI controller has been widely used in industrial applications. If a PI control gain is selected suitable, the PI controller shows very good control performance. But it is very difficult to find the optimal PI control gain. Therefore, in this paper, the 4-rule based fuzzy logic modifier of the conventional PI controller are presented. The fuzzy logic modifier which exhibits a stabilizing effects on the closed-loop system, has good robustness regarding the improperly tuned PI controller. The simulation are performed to verify the capability of proposed control method on vector controlled induction motor drive system.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.230-233
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• 1998

The conventional PI controller are fragile in parameter variation and load-variation. Therefore, in this paper, a speed control algorithm based on the Fuzzy PI controller is proposed for the high performance speed control of a voltage-source inverter to drive 3-phase induction motors. The computer simulation results show that the proposed controller are more excellent control characteristics than conventional PI controller in transient-state and steady-state response.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.93.2-93
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• 2001

This paper presents the implementation of fuzzy PI gain scheduling controller (FPICGS) for controlling flexible joint robot arms with uncertainties from time-varying load. The term FPICGS is called based on a combination of fuzzy PI control scheme with a set of rule bases. Principle of design for a FPICGS is given along with the implementation of the designed computer aided control system. The experiment reveals an effectiveness of the proposed control scheme for flexible joint robot arms driven by a DC motorhooked with a spring which both parameters are completely unknown parameters ...

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1127-1132
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• 1991

Pneumatic control system has been used mainly for endpoint position control because of the compressibility, viscosity and low output stiffness of air which causes nonlinear flow characteristics. In this paper, pneumatic position control algorithms using fuzzy rule were developed to achieve faster and more stable response than conventional PI control algorithm. The performances of the proposed algorithms were compared by computer simulations with them of PI controller. From those simulations it was shown that the proposed algorithms are more efficient about settling time, steady state error and overshoot than PI control algorithm.

• Proceedings of the KIPE Conference
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• 1998.07a
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• pp.200-203
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• 1998

In this paper, it deals with Switched Reluctance Motor(SRM) which has fuzzy logic contoroller(FLC). The modeling and FLC of SRM are presented. The modeling and FLC of SRM are presented. The results of simulation show the speed responce characteristics of SRM with FLC. As a result, the SRM controller with FLC is verified by comparison between PI controller and fuzzy logic controller.