• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.9
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• pp.33-43
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• 2011

Since the fuzzy neural network(FNN) is universal approximators, the development of FNN control systems have also grown rapidly to deal with non-linearities and uncertainties. However, the major drawback of the existing FNNs is that their processor is limited to static problems due to their feedforward network structure. This paper proposes the recurrent FNN(RFNN) for high performance and robust control of SynRM. RFNN is applied to speed controller for SynRM drive and model reference adaptive fuzzy controller(MFC) that combine adaptive fuzzy learning controller(AFLC) and fuzzy logic control(FLC), is applied to current controller. Also, this paper proposes speed estimation algorithm using artificial neural network(ANN). The proposed method is analyzed and compared to conventional PI and FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.754_755
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• 2009

This paper deals with the characteristics analysis & optimum design of Synchronous Reluctance Motor (SynRM) with anisotropy rotor using a coupled Finite Element Method (FEM) & Response Surface Methodology (RSM). The focus of this paper is the characteristics analysis & optimum design relative to the output power on the basis of rotor materials of a SynRM. The coupled Finite Elements Analysis (FEA) & Preisach model have been used to evaluate nonlinear solutions. Comparisons are given with characteristics of normal synchronous reluctance motor and those of anisotropy rotor SynRM (ANISO-SynRM), respectively. The feasibility of using RSM with FEM in practical engineering problem is investigated with computational examples and comparison between the fitted response and the results obtained from an analytical solution according to the design variables of rotor in anisotropy rotor SynRM.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1813-1819
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• 2016

In this paper, LS-SynRM (Line Start-Synchronous Reluctance Motor) has been attracting attention in replace of induction motor which hardly provides high efficiency. Compared to induction motor, LS-SynRM has better efficiency per unit area. This study demonstrated the electromagnetic design methods of LS-SynRM while maintaining the frame of existing IE3 induction motor for blower. We documented the design procedures for generating high saliency which is the most essential and mechanical stress analysis is also treated. In conclusion, we proved the validity of our design by manufacturing and testing our LS-SynRM models.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.257-259
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive learning mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $^{i}d$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.4
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• pp.203-208
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• 2006

This paper presents characteristics of SynRM(Synchronous Reluctance Motor) that is compared with a high speed induction motor. SynRM is much suitable for high speed electric machines because of structural robustness. There are many kinds of SynRM according to the shape of rotors. Particularly, axially laminated anisotropic (ALA) rotor is suitable for high speed instruments. Characteristics of SynRM with ALA rotor is obtained from a governing voltage and torque equation mainly composed of d-axis and q-axis inductance that will be identified with finite element method.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.858-859
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• 2007

This paper deals with the characteristics analysis of Synchronous Reluctance (SynRM) with anisotropy rotor using a coupled FEM & Preisach model. The focus of this paper is the design relative to the output power on the basis of rotor materials of a SynRM. The coupled Finite Elements Analysis (FEA) & Preisach model have been used to evaluate nonlinear solutions. Comparisons are given with characteristics of normal synchronous reluctance motor and those of anisotropy rotor SynRM (ANISO-SynRM), respectively.

• Journal of Power Electronics
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• v.18 no.5
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• pp.1380-1397
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• 2018

The synchronous reluctance motor (SynRM) servo-drive system has highly nonlinear uncertainties owing to a convex construction effect. It is difficult for the linear control method to achieve good performance for the SynRM drive system. The nonlinear backstepping control system using upper bound with switching function is proposed to inhibit uncertainty action for controlling the SynRM drive system. However, this method uses a large upper bound with a switching function, which results in a large chattering. In order to reduce this chattering, a nonlinear backstepping control system using an adaptive law is proposed to estimate the lumped uncertainty. Since this method uses an adaptive law, it cannot achiever satisfactory performance. Therefore, a nonlinear backstepping control system using a reformed recurrent Hermite polynomial neural network with an adaptive law and an error estimated law is proposed to estimate the lumped uncertainty and to compensate the estimated error in order to enhance the robustness of the SynRM drive system. Further, the reformed recurrent Hermite polynomial neural network with two learning rates is derived according to an increment type Lyapunov function to speed-up the parameter convergence. Finally, some experimental results and a comparative analysis are presented to verify that the proposed control system has better control performance for controlling SynRM drive systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.10
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• pp.47-57
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• 2006

The paper is proposed maximum torque control of SynRM drive using adaptive teaming mechanism-fuzzy neural network(ALM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $^i{_d}$ for maximum torque operation is derived. The proposed control algorithm is applied to SynRM drive system controlled ALM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the ALM-FNN and ANN controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.2
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• pp.115-124
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• 2009

This paper proposed an adaptive fuzzy controller for controlling speed and positions of a container crane. The motor used in container crane is installed as SynRM with variable-speed drive having the robustness on the problems of energy and environment. The conventional PI controller is not able to accurately track the position, speed and sway angle of trolley due to the factors of environment and the parameter variety. In the paper, we analyzed the performance of SynRM derive applied to the container crane by using an adaptive fuzzy control of SynRM in order to solve those problems. This paper analyzed the characteristics of position and speed response and compared the performance of PI controller with an adapative Fuzzy controller, proving the validity.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.11
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• pp.35-40
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• 2015

In accordance with global energy conservation policies such as MEPS (Minimum Energy Performance Standard), electric motor industry is moving to super-high-efficiency machines and research to develop IE4 (International Energy Efficiency Class 4) motors has been launched. In this situation, SynRM (Synchronous Reluctance Motor) has been attracting attention in place of induction motor which hardly provides super premium efficiency. As a result, much research on SynRM is being performed at home and abroad. Also, some products have already been appearing in the market. Compared to induction motor, SynRM has better efficiency per unit area and wider operating range. Although the utilization of control system in synchronous motor results in higher prices, we still need to concentrate on developments of SynRM so as to comply with the new policies. This study demonstrated the electromagnetic design methods of super premium SynRM while maintaining the frame of existing IE3 induction motor. We documented the design procedures for generating high saliency which is the most essential and mechanical stress anlaysis is also treated. In conclusion, we proved the validity of our design by manufacturing and testing our 3 models.