• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1648-1654
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• 2016

This paper analyzes complex vector current control for the enhanced cross-coupling compensation in accordance with parameter variation in grid-connected inverter system, and verifies through simulation and experiment. Complex vector current control is performed in the synchronous reference frame through d-q transformation. It generates cross-coupling components with rotating nominal angular frequency. In general, cross-coupling elements are compensated by decoupling terms added to output of conventional decoupling PI controller. But, it is impossible to compensate them perfectly which transient response is especially deteriorated such as large overshoot and slow tracking, when variation of grid impedance or measurement error occurs. However, complex vector current control can improve stability and response characteristic of current control regardless of the situation as before. Decoupling controller and complex vector controller are represented through complex forms, and these controllers are analyzed by using frequency response in s-domain, respectively. It is verified that complex vector controller has more superior response characteristic than decoupling controller through MATALB, PSIM and experimental in 5kW grid-connected inverter when L filter parameter is varied from 1.1mH to increase double, 2.2mH.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.463-471
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• 1999

This paper presents a vector controlled induction motor is implemented by neural networks system compared with PI controller for the speed control. The design employed the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE) for speed. In order to update the weights of the controller First of all Emulator updates its parameters by identifying the motor input and output next it supplies the error path to the output stage of the controller using backpropagation algorithm, As Controller produces an adequate output to the system due to neural networks learning capability Vector controlled induction motor characteristics actual motor speed with based on neural network system follows the reference speed better than that of linear PI speed controller.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.119-121
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• 2008

This paper is proposed a high Performance speed control of the synchronous reluctance motor through the SV-PWM(Space Vector Pulse Width Modulation) of FAM-PI(Fuzzy Adaptive Mechanism-PI). SV-PWM is controlled using FAM-PI control. SV-PWM can be maximum used maximum do link voltage and is excellent control method due to characteristic to reducing harmonic more than others. Fuzzy control has a advantage which can be robustly controlled. FAM-PI controller is changed fixed gain of PI controller using fuzzy adaptive mechanism(FAM) to match operating condition. 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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.233-243
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• 1994

Generally, fuzzy PI controller that regulates the gains using fuzzy algorithm shows high performance in speed response. However, it has some problems to the load inertia variation, because the change of speed error(CE) is in a fixed range. As load inertia increases, CE is decreased and the usuage of fuzzy table is limited. Therefore, the output of the fuzzy controller has a limited range. This paper proposes an improved fuzzy PI controller. To reduce the speed overshoot, we adapt a control method that selects a proper CE range with respect to the load inertia variation. The proposed controller is applied to the vector controlled system with 2.2kW induction motor. Some simulation and experimental results are exhibited. With these results, we can easily find that proposed PI controller is more robust than the conventional fuzzy PI controller against the load inertia variation.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.47-49
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• 2005

This paper presents a robust speed control method of induction motors(IM) using a Non-linear PI controller(NPI), NPI is high gain controller in region of small error, and low gain controller in region of large error. so in steady state, system will be robust against variation of load torque. The simulation and experiment results confirm the validity of proposed control scheme.

• Journal of Industrial Technology
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• v.26 no.B
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• pp.227-231
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• 2006

This paper presents a robust speed control method of induction motors(IM) using a Non-linear PI controller(NPI). NPI is high gain controller in region of small error, and low gain controller in region of large error. So in steady state, system will be robust against variation of load torque. The simulation and experiment results confirm the validity of proposed control scheme.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1155-1157
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• 2002

This paper presents the use of a simple genetic algorithm for the tuning of a proportional-integral speed controller for an induction motor drive. The influence of population size, generation number and rate of mutation on the convergence of the genetic algorithm is investigated. On Matlab/Simulink environment, this paper proposes an optimal GA-PI controller of indirect vector control for induction motor drive system. The simulation results verify that the system has a more robust to the parameter variation than classical PI controller.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.211-214
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• 2000

The conventional PI controller has been widely used in industrial application due to the simple control algorithm. But it is very difficult to find the optimal PI control gain. Therefore in this paper to obtain optimal performance fuzzy proportional-plus-integral controller for the vector control system of an induction machine is presented. The simulation model is created in MATLAB/SIMULINK. The simulation results demonstrate the good performance of this system.

• 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.

• Journal of Industrial Technology
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• v.22 no.B
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• pp.185-190
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• 2002

This paper describes a design of an induction motor control system using a 2 degree-of-freedom PI controller to compensate the effects of disturbance without degrading tracking performance. On the basis of vector control principle, the control system is simulated by using the ACSL and implemented on a DSP system(TMS320C31). In designing the 2 DOF controller, we can tune the performance of either the tracking or disturbance rejection independently without affecting the other. With the experimental results, the 2 DOF controller has shown a better performance in command tracking and disturbance rejection than a conventional PI controller.