• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.503-510
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• 2021

This study intends to apply the mathematical method of fractional order differentiation to a controller that controls the response of the system. Therefore, we design integrator for the fractional index by converting it into discrete time to construct a controller. The IP controller composes an integral controller for errors and the proportional controller applies only the system output. The controller is designed by using the fractional order integrator to the integral controller of the IP controller. First, the performance of the PI controller and the IP controller is compared, and the designed controller is applied to the speed control of the motor. As a result, the motor output speed was uniformed and precise control performance could be obtained. It was confirmed that the speed error in the steady state is within 0.1 [%], and it has precise and uniform speed control performance without overshoot.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.24-31
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• 2007

This paper presents self tuning PI(STPI) controller of IPMSM drive using neural network. In general, PI controller in computer numerically controlled machine process fixed gain. They may perform well under some operating conditions, but not all. To increase the robustness of fixed gain PI controller, STPI controller proposes a new method based neural network. STPI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.58-64
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• 1997

FLC(Fuzzy Logic Controller) is stronger to the disturbance than a classical controller and its overshoot of the intialized value is excellent. In case an unknown process or the mathematical modeling of a complicated system is impossible, a fit control quantity can be acquired by the Fuzzy inference. But FLC can not converge correctly to the desirable value because the FLC's output value by the size of the quantization level of the Fuzzy variable always has a minor error. There are many ways to eliminate the minor error, but I will suggest GA-FLC and EP-FLC Hybrid controller which csombines FLC with GA(Genetic Algorithm) and EP(Evo1ution Programming). In this paper, the output characteristics of this Hybrid controller will be compared and analyzed with those of FLC, it will he showed that this Hybrid controller converge correctly to the desirable value without any error, and !he convergence speed performance of these two kinds of Hyhrid controller also will be compared.

• Journal of Digital Contents Society
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• v.2 no.1
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• pp.51-61
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• 2001

The FLC(Fuzzy Logic Controller) is stronger to the disturbance and has the excellent characteristic to the overshoot of the initialized value than the classical controller, and also can carry out the proper control being out of all relation to the mathematical model and parameter value of the system. But it has the restriction which can't adopt the environment changes of the control system because of generating the fuzzy control rule through an expert's experience and the fixed value of the once determined control rule, and also can't converge correctly to the desired value because of haying the minute error of the controller output value. Now there are many suggested methods to eliminate the minute error, we also suggest the GA-FNNIC(Genetic Algorithm Fuzzy Neural Network Intelligence Controller) combined FLC with NN(Neural Network) and GA(Genetic Algorithm). In this paper, we compare the suggested GA-FNNIC with FLC and analyze the output characteristics, convergence speed, overshoot and rising time. Finally we show that the GA-FNNIC converge correctly to the desirable value without any error.

• Journal of the Microelectronics and Packaging Society
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• v.31 no.3
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• pp.99-104
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• 2024

With the advancement of power electronics technology and the increasing demand for high-efficiency power semiconductors, silicon carbide (SiC) devices have gained attention as an alternative to overcome the limitations of traditional silicon (Si) semiconductors. SiC devices enable excellent switching efficiency due to their high switching speed. However, parasitic inductance within the power module can cause voltage oscillations and overshoot phenomena, potentially leading to issues with electrical reliability and efficiency. To address these challenges, two approaches were proposed and validated. The first approach involved applying an RC snubber circuit to mitigate the effects of parasitic inductance, thereby improving electrical stability. The second approach focused on optimizing the lead-frame design to reduce parasitic inductance. Both methods were verified through simulations and experiments, demonstrating that the electrical reliability and efficiency of SiC power modules can be simultaneously improved.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1833-1837
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• 2004

The two-inertia system, which has the torsion vibration, is typically found in several industrial applications. This torsion vibration will effect the quality of the rolled material as well as the stability of the drive system. Thus the speed and torsion vibration of the system have to be properly controlled. This paper, I-PDA controller designed by Coefficient Diagram Method to control a two-inertia system is proposed. The experimental result shows that both of transient and steady state specification can be fulfilled but the transient response still has long rise time. In order to improve the speed of the system response, a phase lag structure of feedforward controller is introduced to I-PDA control system. It is shown that the performance of the I-PDA control system with suitable FFC has shorter rise and settling times, no overshoot and the torsion vibration can be suppressed.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.310-313
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• 2003

This paper is proposed new fuzzy controller for high performance of interior permanent magnet synchronous motor (IPMSM) drive New fuzzy controller take out appropriate amounts of accumulated control input according to fuzzy described situations in addition to the incremental control input calculated by conventional direct fuzzy controller. The structures of the proposed controller is motivated by the problems of direct fuzzy controller. The direct controller generally give inevitable overshoot when one tries to reduce rise time of response especially when a system of order higher than one is under consideration. The undesirable characteristics of the direct fuzzy controller are caused by integrating operation of the controller, even though the integrator itself is introduced to overcome steady state error in response. Proposed controller fuzzy clear out integrated quantities according to situation. This paper attempts to provide a thorough comparative insight into the behavior of IPMSM drive with direct and new fuzzy speed controller. The validity of the comparative results is confirmed by simulation results for IPMSM drive system.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.91-93
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• 2007

This paper presents multi-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, fred gain PI controller, Multi-PI controller proposes a new method based fuzzy and neural-network. Multi-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. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.12
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• pp.9-20
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• 2012

This paper proposes the efficiency optimization control of interior permanent magnet synchronous motor(IPMSM) drive using series connected-fuzzy neural network PI(SC-FNPI) controller. The PI controller is generally used to control IPMSM drive in industrial field. However, the PI controller has problem which is falling control performance about parameter variation such as command speed, load torque and inertia due to fixed gain of PI controller. Therefore, to improve performance of PI controller, this paper proposes SC-FNPI controller adjusted input of PI controller by FNN controller according to operating conditions. Also, this paper proposes efficiency optimization control which is improving efficiency with minimize loss. The SC-FNPI controller proposed in this paper is compared control performance with conventional FNN and PI controller about command speed, load torque and inertia variation. And the efficiency optimization control is compared with $i_d=0$ control about loss and efficiency. The SC-FNPI controller proposed in this paper shows more excellent control performance for rising time, overshoot and steady-state error. Also efficiency optimization control is increased efficiency by reducing loss.

• Journal of Biosystems Engineering
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• v.37 no.2
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• pp.106-112
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• 2012

Purpose: A lab-scale timber carriage using a servo motor system was built. When two motors move a carriage, wire tension is changed according to the different line speeds caused by a wire drum's changing diameter, leading to inappropriate traveling characteristics of the carriage. In order to overcome this problem, PID Control was used to control the motor speed. Methods: Ziegler-Nichols method was used to determine PID gains. Results: The initial PID gains were 1.8, 0.025, and 0.006, respectively, and optimal gains of 1.4 and 0.010 for P and I gain were obtained experimentally. Conclusions: The results showed that constant wire tension could be maintained by controlling the speed of the motor using PI control. Overshoot occurred at initial motor operation due to vibration and elasticity of the wire itself.