• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.12
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• pp.2103-2108
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• 2007

This study investigates the dynamic characteristics of Synchronous Reluctance Motor (SynRM), with segmental rotor structure, using finite element method in which the moving mesh technique is considered. The focus of this paper is the efficiency of on-line parameter identification system for position sensorless control of a SynRM considering saturation and iron loss. Comparisons are given with angle of the observer and those of proposed FEM & Preisach model of synchronous reluctance motor, respectively. The position sensorless control using identified motor parameters is realized, and the efficiency of the on-line parameter identification system is verified by experimental results.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.3
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• pp.282-290
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• 2001

The accurate identification of the motor parameters is crucially important to achieve high dynamic performance of induction motors. In this paper, th motor parameters such as stator(rotor) resistance, stator(rotor) leakage inductance, mutual inductance, and rotor inertia are measured in off-line. Stator(rotor) resistance and stator(rotor) leakage inductance are measured based on the stationary coordinate equations of induction motors. On the other hand, mutual inductance are measured under the scalar control. Finally, the inverse rotor time constant is identified in on-line using an extended kalman filter algorithm. To demonstrate the practical significance of the results, Some experimental results are presented.

• Journal of Electrical Engineering and Technology
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• v.10 no.6
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• pp.2262-2270
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• 2015

Generally, internal parameters of the motors and generators can be divided to the resistance and inductance components. They can become a cause of the changing internal parameters because they have sensitive characteristics due to external conditions. The changed parameters can generate the outputs which include error values from the speed and current controllers. Also, it can bring the temperature increase and mechanical damage to the system. Therefore, internal parameters of the motors and generators need to obtain their values according to the external conditions because it can prevent the mechanical damage caused by the changed parameters. In this paper, the off-line parameter identification method is verified using the Goertzel algorithm. The motor used in the simulation and experiments is an interior permanent magnet synchronous motor (IPMSM), and the proposed algorithm is verified by the simulation and experimental results.

• Journal of international Conference on Electrical Machines and Systems
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• v.1 no.2
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• pp.3-9
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• 2012

The paper describes a novel technique for on line parameter identification of three-phase induction motors from a single, run up to speed test. Data is sampled during this test with the normal locked rotor and synchronous speed data captured on the way to reaching the motor's rated speed. Rotor parameter variations with frequency due to skin and proximity effects and other non-linear imperfections such as heating and main flux path saturation are taken into account. This method is ideal for determining and/or verifying parameters used in high performance drives.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2000.11a
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• pp.199-204
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• 2000

Generally, The systems are so complex that it not possible to obtain reasonable model using physical insight. Also a model based on physical insight contains a number of unknown parameters even if the structure is derived from physical laws. To solve these problems, the systems identification is described in this paper. So, AC servo motor system which has both open loop and closed loop is selected as an example for identification. A state-space model of AC servo motor system is identified through open loop experiment and identified through closed loop experiment and using pole placement integral controller to open loop system. As the results, From ARMA model, We have obtained continuous-time state space model.

• Proceedings of the KIEE Conference
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• 1998.07f
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• pp.2008-2011
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• 1998

When the vector control, which does not need a speed signal from a mechanical speed sensor, it is possible to reduce the cost of the control equipment and to improve the control performance in many industrial application. This paper describes a rotor speed identification method of induction motor based on the theory of Model Reference Adaptive System(MRAS). The identifier execute the rotor speed identification so that the vector control of the induc-tion motor may be achieved. The improved auxiliary variable are introduce to perform accurate rotor speed identification. Simulation and experimental result show the validity of the proposed control method.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.723-725
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• 2000

This paper presents a parameter identification method to estimate the stator resistance. stator inductance, rotor resistance and rotor inductance of the induction motor. A step voltage is applied across the stator terminals while the machine is in the standstill condition, and the resulting stator voltage and current response are measured. Observer/Kalman Filter Identification(OKID) algorithm is used to estimate induction motor parameters. Simulation results are presented to verify the identified model.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.852-854
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• 1995

This paper proposes a new identification method that utilizes fuzzy inference in parameter identification. The prosed system has an additional control loop where a real plant has replaced by a plant model. Fuzzy rules describe the relationship between comparison results of the features and magnitude of modification in the model parameter values. In this paper, the tuning method which determines parameters of PID controller automatically is described through applying this algorithm to DC servo motor. And we intend to investigate effectiveness of the method by experiments. This method is effective in auto-tuning because the response of the closed loop has verified. The simulated and the experimental results of the dc servo motor are shown to confirm the viability of this method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.2
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• pp.352-359
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• 2008

This paper presents a controller implementation using model based controller design programs-System Identification Toolkit, Control Design Toolkit, Simulation module. This method is easier and simpler than conventional controller design method. To implement speed control system of DC motor, a CompactRIO, Real-Time(RT) cntroller provided by NI(National Instruments), is used as hardware equipment. Firstly transfer function of DC motor drive system, which was a control target plant, can be acquired through System Identification Toolkit by using test input signal applied to motor and output signal from motor. And designing of pole-zero compensator satisfying desired control response performance through Control Design Toolkit, designed speed control response can be tested through Simulation Module. Finally LabVIEW program is converted to real-time program and downloaded to CompactRIO real-time controller Through experimental results to real DC motor drive system, designed speed control response is compared to simulation results.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1566-1577
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• 2018

This paper presents a stability analysis of AC-DC power system feeding a speed controlled DC motor in which this load behaves as a constant power load (CPL). A CPL can significantly degrade power system stability margin. Hence, the stability analysis is very important. The DQ and generalized state-space averaging methods are used to derive the mathematical model suitable for stability issues. The paper analyzes the stability of power systems for both speed control natural frequency and DC-link parameter variations and takes into account controlled speed motor dynamics. However, accurate DC-link filter and DC motor parameters are very important for the stability study of practical systems. According to the measurement errors and a large variation in a DC-link capacitor value, the system identification is needed to provide the accurate parameters. Therefore, the paper also presents the identification of system parameters using the adaptive Tabu search technique. The stability margins can be then predicted via the eigenvalue theorem with the resulting dynamic model. The intensive time-domain simulations and experimental results are used to support the theoretical results.