• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.67-69
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• 2007

PMSM (Permanent Magnet Synchronous Motor) current control is a most inner loop of electromechanical driving systems and it plays a foundation role in the hierarchy's control loop of several mechanical machine systems. In this paper, a simple RMRAC control scheme for the PMSM is proposed in the synchronous frame. In the synchronous current model, the input signal is composed of as a calculated voltage by adaptive laws and system disturbances. The gains of feed-forward and feed-back controller are estimated by the proposed e-modification methods respectively, where the disturbances are assumed as filtered current tracking errors. After the estimation of the disturbances from the tracking errors, the corresponding voltage is fed forward to control input to compensate for the disturbances. The proposed method is robust to high frequency disturbances and has a fast dynamic response to time varying reference current trajectory. It also shows a good real-time performance duo to it's simplicity of control structure. Through the simulations considering several cases of external disturbances and experimental results, efficiency of the proposed method is verified

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.347-353
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• 2003

A nonlinear speed controller for a surface mounted permanent magnet synchronous motor (PMSM) based on a newly developed adaptive backstepping approach is presented To compensate parameter uncertainties and load torque disturbance, a nonlinear adaptive backstepping control law and adaptive law are derived systematically through virtual control input and suitable Lyapunov function. Also, speed observer without using costly speed sensor is presented. Simulation results show that the proposed controller can observe the speed and track the reference speed signal generated by a reference model.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.425-436
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• 2016

In this paper, a parameter optimization based iterative learning control strategy is presented for permanent magnet synchronous motor control. This paper analyzes the mechanism of iterative learning control suppressing PMSM torque ripple and discusses the impact of controller parameters on steady-state and dynamic performance of the system. Based on the analysis, an optimization problem is constructed, and the expression of the optimal controller parameter is obtained to adjust the controller parameter online. Experimental research is carried out on a 5.2kW PMSM. The results show that the parameter optimization based iterative learning control proposed in this paper achieves lower torque ripple during steady-state operation and short regulating time of dynamic response, thus satisfying the demands for both steady state and dynamic performance of the speed regulating system.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.220-222
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• 2002

DG (Distributed Generation) devices such as co-generation systems, fuel cells and photovoltaic power generation systems, etc is introducing into the distribution systems by the deregulation. In this paper, the controller of synchronous generator used for DG is newly designed in order to regulate the real & reactive power and the effect on the islanding phenomenon compared with the traditional controller.

• Journal of IKEEE
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• v.22 no.3
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• pp.716-722
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• 2018

This paper presents a voltage angle control strategy for surface permanent magnet synchronous motor (SPMSM) drives used in low-cost applications, wherein a current vector control is not employed. In the proposed method, the current vector control scheme, which requires high precision phase-current sensing units and a fast calculation capability of a motor drive controller, is replaced with the voltage angle controller. The proposed voltage angle controller calculates a d-axis voltage command to make the d-axis current zero by using a simple equation obtained from the voltage equation of SPMSM. The proposed method shows performance similar to the current vector controlled SPMSM drive during steady-states and its structure is very simple and thus it can be easily implemented with a low-cost microcontroller. The effectiveness of the proposed method is verified through simulations and experiments.

• Journal of Power Electronics
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• v.9 no.2
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• pp.207-214
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• 2009

This paper presents a modem approach for speed control of a PMSM using the Particle Swarm Optimization (PSO) algorithm to optimize the parameters of the PI-Controller. The overall system simulated under various operating conditions and an experimental setup is prepared. The use of PSO as an optimization algorithm makes the drive robust, with faster dynamic response, higher accuracy and insensitive to load variation. Comparison between different controllers is achieved, using a PI controller which is tuned by two methods, firstly manually and secondly using the PSO technique. The system is tested under variable operating conditions. Implementation of the experimental setup is done. The simulation results show good dynamic response with fast recovery time and good agreement with experimental controller.

• Journal of Power System Engineering
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• v.8 no.4
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• pp.17-23
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• 2004

A delivery ship is used to handle the cargo with the crane to/from the ships. The ship is inclined in the direction of a cargo which is hung on a crane. In this case, a arc shaped rail should be in the equilibrium state to get good anti rolling performance. In this study, a device and control algorithm are developed to take accurate and quick equilibrium of the rail. The device is composed of a hinged immovable support and two screw jacks. And the control algorithm demands two controllers. One controller is designed such that the screw jack 1 and 2 follow the position reference signal generated by a tilt sensor. The other controller of two degree of freedom is designed to remove the synchronous error occurred between jack 1 and jack 2. The simulation results show that the desirable control performance is achieved.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.10
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• pp.579-586
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• 1999

This paper describes a simulation model and a scaled hardware model to analyze the dynamic performance of Unified Power Flow Controller, which can flexibly adjust the active power flow through the ac transmission line. The design of control system for UPFC was developed using vector control method. The results of simulation and scaled hardware test show that the developed control system works accurately. Both models would be very effective for analyzing the dynamic performance of the Unified Power Flow Controller.

• Journal of Power Electronics
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• v.18 no.1
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• pp.103-115
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• 2018

Parametric uncertainties and inverter nonlinearity exist in the permanent magnet synchronous motor (PMSM) drive system of electrical vehicles, which may lead to performance degradation or failure, and eventually threaten reliable operation. Therefore, a model-free deadbeat predictive current controller (MFDPCC) for PMSM drive systems is proposed in this study. The data-driven ultra-local model of a surface-mounted PMSM (SMPMSM) drive system that consists of parametric uncertainties and inverter nonlinearity is first established through the input and output data of a SMPMSM drive system. Subsequently, MFDPCC is designed. The performance comparisons and analyses of the proposed MFDPCC, the conventional proportional-integral controller, and the model-based deadbeat predictive current controller for SMPMSM drive systems are implemented via system simulation and experimental tests. Results show the effectiveness and technical advantages of the proposed MFDPCC.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.175-177
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• 2005

An interior permanent magnet synchronous motor (IPMSM) is receiving increased attention for many industrial applications because of its high torque to inertia ratio, superior power density, and high efficiency. This paper presents algorithm for speed sensorless vector control based on a fuzzy controller and an instantaneous reactive power. Effectiveness of algorithm is confirmed by the experiments.