• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.21 no.5
• /
• pp.32-43
• /
• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current and voltage rated value. This paper proposes speed control of IPMSM using adaptive learning fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive learning fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive learning fuzzy neural network and artificial neural network.

• Journal of Power Electronics
• /
• v.3 no.2
• /
• pp.99-114
• /
• 2003

This paper presents a feasible development on a highly accurate quick response adjustable speed drive implementation fur general purpose induction motor which operates on the basis of sensorless slip frequency type vector controlled sine-wave PWM inverter with an automatic tuning machine parameter estimation schemes. In the first place, the sensorless vector control theory on the three-phase voltage source-fed inverter induction motor drive system is developed in slip frequency based vector control principle. In particular, the essential procedure and considerations to measure and estimate the exact stator and rotor circuit parameters of general purpose induction motor are discussed under its operating conditions. The speed regulation characteristics of induction motor operated by the three-phase voltage-fed type current controlled PWM inverter using IGBT's is illustrated and evaluated fur machine parameter variations under the actual conditions of low frequency and high frequency operations for the load torque. In the second place, the variable speed induction motor drive system, employing sensorless vector control scheme which is based on three -phase high frequency carrier PWM inverter with automatic toning estimation schemes of the temperature -dependent and -independent machine circuit parameters, is practically implemented using DSP-based controller. Finally, the dynamic speed response performances for largely changed load torque disturbances as well as steady state speed vs. torque characteristics of this induction motor control implementation are illustrated and discussed from an experimental point of view.

• Journal of Korean Society of Transportation
• /
• v.28 no.1
• /
• pp.87-96
• /
• 2010

The impact speed estimation practice used in the car-bicycle accident analysis practice in Korea was mainly dependent on foreign study results which were tested with limited speed ranges and vehicle types, but the characteristics of roadway, human body, and vehicle performance were quite different. This study developed an impact speed estimation model using the car-bicycle accident field data. For this, a regression analysis was performed using the impact speed and bicycle throw distance collected from 23 real accident data, and statistical test was also conducted. For the verification of the induced model, the impact speeds derived from the model were compared with the true impact speeds estimated from skid marks of two accident cases. The result showed that the two speeds were very close to each other. It is believed that the model could be included in the car-bicycle accident analysis practice.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.1
• /
• pp.155-161
• /
• 2021

Recently, researches for military purposes such as precision tracking and mission completion using UAVs have been actively conducted. In particular, if the posture information of the leading UAV is estimated and the mission UAV uses this information to follow in stealth and complete its mission, the speed of the posture information estimation of the guide UAV must be processed in real time. Until recently, research has been conducted to accurately estimate the posture information of the leading UAV using image processing and Kalman filters, but there has been a problem in processing speed due to the sequential processing of the processing process. Therefore, in this study we propose a way to improve processing speed by applying methods that the image processing area is limited to the ROI area including the object, not the entire area, and the continuous processing is distributed to OpenMP-based multi-threads and processed in parallel with thread synchronization to estimate attitude information. Based on the experimental results, it was confirmed that real-time processing is possible by improving the processing speed by more than 45% compared to the basic processing, and thus the possibility of completing the mission can be increased by improving the tracking and estimating speed of the mission UAV.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2009.10a
• /
• pp.355-358
• /
• 2009

This paper proposes efficiency optimization control of IPMSM drive using multi hybrid fuzzy controller(HFC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on HFC using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using multi HFC. Also, this paper proposes speed control of IPMSM using HFC1, current control of HFC2-HFC3 and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HFC, the operating characteristics controlled by efficiency optimization control are examined in detail.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.60 no.9
• /
• pp.1700-1707
• /
• 2011

Interior permanent magnet synchronous motor(IPMSM) adjustable speed drives offer significant advantages over induction motor drives in a wide variety of industrial applications such as high power density, high efficiency, improved dynamic performance and reliability. Since the fuzzy neural network(FNN) is recognized general approximate method to control non-linearities and uncertainties, the development of FNN control systems have also grown rapidly. The FNN controller is compounded of fuzzy and neural network. It has an advantage that is the robustness of fuzzy control and the ability to adapt of neural network. However, the FNN has static problem due to their feed-forward network structure. This paper proposes high performance speed control of IPMSM drive using the recurrent FNN(RFNN) which improved conventional FNN controller. The RFNN has excellent dynamic response characteristics because of it has internally feed-back structure. Also, this paper proposes speed estimation of IPMSM drive using ANN. The proposed method is analyzed and compared to conventional FNN controller in various operating condition such as parameter variation, steady and transient states etc.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.9 no.5
• /
• pp.467-477
• /
• 2004

A new scheme to estimate the moment of inertia in the servo motor drive system in very low speed is proposed in this paper. The typical speed estimation scheme in most servo system for low speed operation is sensitive to the variation of machine parameters, especially the moment of inertia. To estimate the motor inertia value, the observer using the Radial Basis Function Networks(RBFN) is applied. The effectiveness of the proposed inertia estimation method is verified by experiments. It is concluded that the speed control performance in the low speed region is improved with the proposed disturbance observer using RBFN.

• Proceedings of the KIEE Conference
• /
• 2006.10b
• /
• pp.131-135
• /
• 2006

In this paper, a new estimation algorithm for the rotor speed for SRM drives is described. The algorithm is implemented by the binary observer. The stability and robustness of the binary observer for the parameter variations of the SRM are Proved by variable structure control theory. Variable speed control of the SRM is accomplished by the estimated speed. Experiment results verify that the MRAS observer is able to estimate the speed.

• Proceedings of the KIPE Conference
• /
• 1996.06a
• /
• pp.1-4
• /
• 1996

The purpose of this treatise is to estimate speed of an induction motor and realize a robust speed control system with estimated speed in field-weakening region. A speed estimation is based on Model Reference Adaptive System(MRAS) technique and two flux estimator are designed to be robust against parameter variation. The MRAS-based overall control scheme has been implemented on 7.5kW Spindle induction motor control system. And it is verified that the proposed control scheme is very stable and robust in field-weakening region.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
• /
• 2001.11a
• /
• pp.181-185
• /
• 2001

This paper presents a digitally speed sensorless control system for induction motor with direct torque control (DTC). The drive is based on Mode1 Reference Adaptive System (MRAS) using state observer as a reference model fat flux estimation. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, model reference adaptive control (MRAS) with rotor flux linkages for the speed turning aignal at low speed range, two hysteresis controllers. The Proposed system is verified through simulation.