• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1945-1955
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• 2018

High frequency signal injection (HFI) is an alternative method for estimating rotor position of interior permanent magnet synchronous motor (IPMSM). The general method of frequency and amplitude selection is based on error tolerance and experiments, and is usually set with only one group of HF parameters, which is not efficient for different working modes. This paper proposes a novel rotor position estimation scheme by HFI with optimized frequency and amplitude, based on the mathematic model of IPMSM. The requirements for standstill and low-speed operational modes are met by applying this novel scheme. Additionally, the effects of the frequency and amplitude of the injected HF signal on the position estimation results under different operating conditions are analyzed. Furthermore, an optimization method for HF parameter selection is proposed to make the estimation process more efficient under different working conditions according to error tolerance. The effectiveness of the propose scheme is verified by the experiments on an IPMSM motor prototype.

• Proceedings of the KIPE Conference
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• 2010.07a
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• pp.600-601
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• 2010

This paper presents the superheater dynamic modeling and parameter estimation for the thermal plant boiler. The temperature control is closely related to the power plant efficiency and boiler life. The dynamic modeling of the superheater and desuperheater is essentially needed and developed by using the heat balance principle. The simulated model outputs are well matched with the actual ones. It is expected that the proposed model is useful for the temperature controller design.

• Journal of Power Electronics
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• v.10 no.5
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• pp.491-497
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• 2010

This paper proposes an estimation algorithm for the electrical parameters of synchronous reluctance motors (SynRMs) by using a synchronous PI current regulator at standstill. In reality, the electrical parameters are only measured or estimated in limited conditions without fully considering the effects of the switching devices, connecting wires, and magnetic saturation. As a result, the acquired electrical parameters are different from the real parameters of the motor drive system. In this paper, the effects of switching devices, connecting wires, and the magnetic saturation are considered by simultaneously using the short pulse and closed loop equations of resistance and synchronous inductances. Therefore, the proposed algorithm can be easily and safely implemented with a reduced measuring time. In addition, it does not need any external or additional measurement equipment, information on the motor's dimensions, and material characteristics as in the case of FEM. Several experimental results verify the effectiveness of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.7 no.5
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• pp.653-658
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• 2012

Load modeling has a significant influence on power system analysis and control. In recent years, measurement-based load modeling has been widely practiced. In the load modeling algorithm, the model structure is determined and the parameters of the established model are estimated. For parameter estimation, least-squares optimization method is applied. The model parameters are estimated so that the error between the measured values and the predicted values is to be minimized. By introducing sliding window concept, on-line load modeling method can be performed which reflects the dynamic behaviors of loads in real-time. For the purpose of data acquisition, the measurement system including PMU is implemented in university level. In this paper, case studies are performed using real PMU data from Korea Univ. and Seoul National University of Science and Technology. The performances of modeling real and reactive power behaviors using exponential and ZIP load model are evaluated.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.10
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• pp.1861-1868
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• 2008

In this paper, Passive Telemerty RF Sensor System using Unscented Kalman Filter algorithm(UKF) is proposed. General Passive Telemerty RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Passive Telemerty RF Sensor System adopts Integrated Circuit type, but there are defects like complexity of structure and limit of large power consumption in some cases. In order to overcome these kinds of faults, Passive Telemetry RF Sensor System based on inductive coupling principle is proposed in this paper. Because passive components R, L, C have stray parameters in the range of high frequency such as about 200[KHz] used in this paper, Passive Telemetry RF Sensor System considering stray parameters has to be derived for accurate model identification. Proposed Passive Telemetry RF Sensor System is simple because it consists of R, L and C and measures the change of environment like pressure and humidity in the type of capacitive value. This system adopted UKF algorithm for estimation of this capacitive parameter included in nonlinear system like Passive Telemetry RF Sensor System. For the purpose of obtaining learning data pairs for UKF Algorithm, Phase Difference Detector and Amplitude Detector are proposed respectively which make it possible to get amplitude and phase between input and output voltage. Finally, it is verified that capacitive parameter of proposed Passive Telemetry RF Sensor System using UKF algorithm can be estimated in noisy environment efficiently.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.4
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• pp.350-357
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• 2005

This paper presents a mechanical sensorless vector-controlled system with parameter identification by the aid of image processor. Based on the flux observer and the model reference adaptive system method, the proposed sensorless system includes rotor speed estimation and stator resistance identification using flux errors. Since the mathematical model of this system is constructed in a synchronously rotating reference frame, a linear model is easily derived for analyzing the system stability, including motor operating state and parameter variations. Because it is difficult to identify rotor resistance simultaneously while estimating rotor speed, a low-accuracy image processor is used to measure the mechanical axis position for calculating the rotor speed at a steady-state operation. The rotor resistance is identified by the error between the estimated speed using the estimated flux and the calculated speed using the image processor. Finally, the validity of this proposed system has been proven through experimentation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.393-402
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• 1990

An iterative learning contol method is presented for a class of linear periodic systems, in which a parameter estimator of the system together with an inverse system model is utilized to generate the control signal at each iteration. A convergence proof is given and two numerical examples are illustrated to show the validities of the algorithm. In particular, it is shown that the method is useful for the continuous path control of robot manipulators.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.2012-2015
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• 2010

In this paper, the mathematical models of the superheater and the desuperheater are derived based on the fundamental laws of physics, mass and energy balance. The parameters of the models are developed for the 500[MW] thermal power plant using the actual data. The simulated model outputs are well matched with the actual ones. It is expected that the proposed models are useful for the temperature controller design of the thermal power plant.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.386-391
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• 1998

Parameter estimation method of induction motor for vector control is presented in this paper. It can be easily implemented and applied to inverters in the industrial field, because it needs no additional hardware such as voltage sensors and measuring equipment. The proposed algorithm in this paper is so straightforward and practical that it can be easily implemented on the built-in controllers with little overhead. The proposed estimation algorithm has good accuracy and repeatability for parameters due to the sensitivity of estimation errors. This enables its total consuming time to be made shorter. Experimental results and applications in the industrial fields verify the validity and usefulness of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2542-2547
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• 2005

In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.