• Journal of Power Electronics
• /
• v.9 no.3
• /
• pp.499-506
• /
• 2009

In this paper, the initial pole-position estimation of a surface (non-salient) permanent magnet synchronous motor is mathematically analyzed and surveyed on the basis of simulation analysis, and developed for accurate servo motor drive. This algorithm is well carried out under the full closed-loop position control without any pole sensors and is completely insensitive to any motor parameters. This estimation is based on the principle that the initial pole-position is simply calculated by the reverse trigonometric function using the two feedback currents in the full closed-loop position control. The proposed algorithm consists of the predefined reference position profile, the information of feedback currents, speed, and relative position, and the reverse trigonometric function for the initial-pole position estimation. Comparing with the existing researches, the mathematical analysis is introduced to get a more accurate initial pole-position of the surface permanent magnet motor under the closed-loop position control. It is found that the proposed algorithm can be easily applied in servo drive applications because it satisfies the following user's specifications; accuracy and moving distance.

• Journal of Power Electronics
• /
• v.15 no.4
• /
• pp.974-986
• /
• 2015

A novel inverter fault-tolerant control scheme is proposed to drive brushless DC motor. A fault-tolerant inverter and its three fault-tolerant schemes (i.e., phase A fault-tolerant, phase B fault-tolerant, and phase C fault-tolerant) are analyzed. Eight voltage vectors are summarized and a voltage vector selection table is used in the control scheme to improve the midpoint current of the split capacitors. A stator flux observer is proposed. The observer can improve flux estimation, which does not require any speed adaptation mechanism and is immune to speed estimation error. Global stability of the flux observer is guaranteed by the Lyapunov stability analysis. A novel stator resistance estimator is incorporated into the sensorless drive to compensate for the effects of stator resistance variation. DC offset effects are mitigated by introducing an integral component in the observer gains. Finally, a control system based on the control scheme is established. Simulation and experiment results show that the method is correct and feasible.

• Proceedings of the KIPE Conference
• /
• 2001.10a
• /
• pp.773-778
• /
• 2001

This paper describes the implementation of the vector control schemes for a variable-speed 131kW PMSM (Permanent Magnet Synchronous Motor) in super-high speed application. The vector control with synchronous reference frame current regulator has been implemented with the challenging requirements such as the extremely low stator inductance$(28^{\mu}H)$, the high dc link voltage(600V) and the high excitation frequency(1.2kHz). Because the conventional position sensor is not reliable in super-high speed, a vector control scheme without any position sensor has been proposed. The proposed sensorless algorithm is implemented by processing the output voltage of the PI current regulator, and hence the structure is simple and the estimated speed is robust to the measurement noise. The experimental system has been built and the proposed control has been implemented and evaluated. The test result, up to the speed of 60,000 r/min, shows the validity of the proposed control.

• Proceedings of the KIEE Conference
• /
• 2007.10c
• /
• pp.123-125
• /
• 2007

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN)controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of induction motor using FLC-FNN and estimation of speed using ANN controller. This paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.9 no.6
• /
• pp.41-48
• /
• 1995

In field oriented control of Induction motors, speed sensor is required, which reduces the sturdiness of drive system and together with the expenditure of hardware for faultless transmission and processing of sensor signals it causes considerable expenses. These expensive sensors can be replaced by speed sensorless concept. And for good control, the knowledge of the rotor flux component or the rotor resistance are needs. Thus, this paper is based on a Extended Kalman Filter (EKF) that estimates the state variables that are required for the control by only measuring the line voltages and currents of the machine. the rotor time constant and speed estimated by the EKF show satisfactory agreement with the real values, with the simulation approaches.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.57 no.3
• /
• pp.244-249
• /
• 2008

This paper deals with speed control of DC servo motor using a Fuzzy tuning observer. Speed sensor detect a speed of rotor continuously. But it have a limit as a driving speed to detect speed precisely. So it is problem to improve the performance of the driving system. To solve the problem, it is studied to detect a speed of DC motor without sensor. In particular, study on the method to estimate the speed using the observer is performed a lot. In this parer, the gain of the observer is properly set up using the fuzzy observer. The fuzzy observer has a superior transient characteristic and is easy to implement compared the existing method is designed. It estimate the derivative of the armature current directly using the armature current measured in the DC motor. It estimate the speed of the rotor using the differentiation. It is proposed speed sensorless control method using the estimated speed. Optimal gain of Luenberger observer is set up using the fuzzy observer and adapted speed control of DC servo motor low speed operation. It is proved excellence and feasibility of the presented observer from the comparison tested a case with a speed sensor and a case without a speed sensor which used a highly efficient drive and 200W DC servo motor starting system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.12
• /
• pp.2708-2715
• /
• 2012

This paper proposes a new sensorless speed control scheme of induction motor using Model Reference Adaptive Control and Direct Torque Control System. The Model Reference Adaptive Control System is based on the comparison between the outputs of Reference Model and Adjustable Model. The error between the estimated quantities obtained by the two models is used to drive a suitable adaptation mechanism which generates the estimated rotor speed for the Adjustable Model. And the Direct Torque Control scheme controls torque and flux by restricting the flux and torque errors within respective hysteresis bands, and motor torque and flux are controlled by the stator voltage space vector using optimum inverter switching table. The simulation results of proposed method indicate good speed responses from the low speed range to the high, and also show favorable characteristics of load operation.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.5
• /
• pp.427-436
• /
• 2002

This paper presents an implementation of high-dynamic performance of position sensorless motion control system of Reluctance Synchronous Motor(RSM) drives for an industrial servo system with direct torque control(DTC). The problems of high-dynamic performance and maximum efficiency RSM drives controlled by DTC are saturation of stator linkage flux and nonlinear inductance characteristics with various load currents. The accurate estimation of the stator flux and torque are obtained using stator flux observer of which a saturated inductance $L_d$ and $L_q$ can be compensated by adapting from measurable the modulus of the stator current and rotor position. To obtain fast torque response and maximum torque/current with varying load current, the reference command flux is ensured by imposing $I_{ds} = I_{qs}$. This control strategy is proposed to achieve fast response and optimal efficiency for RSM drive. In order to prove rightness of the suggested control algorithm, the actual experiment carried out at $\pm$20 and $\pm$1500 rpm. The developed digitally high-performance motion control system shown good response characteristic of control results and high performance features using 1.0kW RSM which has 2.57 Ld/Lq salient ratio.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.7 no.8
• /
• pp.1743-1750
• /
• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.

• Journal of the Korean Society of Industry Convergence
• /
• v.2 no.2
• /
• pp.91-102
• /
• 1999

The paper describes a robust adaptive control algorithm for induction motor drive without speed sensor at low speed range. The control algorithm use only current sensors in a space vector pulse width modulation within loop control with rotor speed estimation and voltage source inverter. On-line rotor speed estimation is based on utilizing parallel model reference adaptive control system. MRAC of the modified flux model for flux and rotor speed estimator uses dual-adaptation mechanism, ${\omega}_r$ and ${\omega}_e$ scheme. The estimated flux components in the model can be compensated from the effects of offset errors on pure integrals. It can be compensated to the parameter variations and torque fluctuation with speed estimation in less then 10 rad/sec. In a simulation, the proposed induction motor control algorithm without speed sensor at very low speed range are shown to operate very well in spite of variable rotor time constant and fluctuating load without change the controller parameters. The suggested control strategy and estimation method have been validated by simulation study, and it proposed the designed system for the implementation using TI320C31 DSP/ASIC controller.