• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.128.3-128
• /
• 2001

In this paper we proposed that the speed of induction motor is controlled by a PI controller, which could control unknown motor using Neural Network for auto-tuning of the PI parameter. The parameters of the PI controller were adjusted to reduce the speed error of the controlled motor. The input parameters of the Neural Network controller are the speed, q-axis current, and speed reference of the induction motor respectively. The usefulness of proposed controller will be confirmed by simulation which we compare with conventional PI controller.

• Journal of Power Electronics
• /
• v.8 no.3
• /
• pp.210-216
• /
• 2008

This paper presents a classical speed controller (CSC) for vector controlled induction motors. The controller explores the use of a Fuzzy Logic controller in a classical form. The controller combines the advantages of the classical controller and the properties of intelligent controllers. The Fuzzy Logic controller idea is used to obtain the CSC output equation, whereby the CSC equation is based on the speed error and its change. The CSC parameters are calculated based on the motor mechanical equation and a predefined system performance. Once the CSC parameters are obtained, the defined speed performance can be achieved at all operating conditions. The application of the CSC to control the speed of a vector controlled induction motor is presented. Different induction motor ratings are used. Simulation results in all possible olperating conditions are presented. Results show that the CSC behaves as an expert controller to provide the predefined speed performance in all possible operating conditions. Based on the results obtained in this paper, the CSC is expected to become the ultimate solution for high-performance drives of the next generation.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.59 no.10
• /
• pp.1797-1802
• /
• 2010

This paper proposes a new fuzzy speed controller based on the Takagi-Sugeno fuzzy method to achieve a robust speed control of a permanent magnet synchronous motor(PMSM). The proposed controller requires the information of the load torque, so the second-order load torque observer is used to estimate it. The LMI condition is derived for the existence of the proposed fuzzy speed controller, and the LMI parameterization to calculate the gain matrices of the controller is provided. It is proven that the augmented control system including the fuzzy speed controller and the load torque observer is exponentially stable. To evaluate the performance of the proposed fuzzy speed controller, the simulation and experimental results are presented under motor parameter and load torque variations. Finally, it is clearly verified that the proposed control method can be used to accurately control the speed of a permanent magnet synchronous motor.

• Journal of Power Electronics
• /
• v.8 no.3
• /
• pp.268-274
• /
• 2008

This paper presents a proposed position controller for a vector controlled induction motor. The position controller design depends on the rotational motion equations and a classical speed controller (CSC) performance. The CSC is designed to have the ability to track variable reference inputs and to provide a predefined system performance. Standard position controller in industry is presented to analyze its performance and its drawbacks. Then the proposed position controller is designed, based on the well defined rotational motion equations. The proposed position controller and the CSC are applied to control the position and speed of the vector controlled induction motor with different ratings. Simulation results at different operating conditions are presented to evaluate the proposed controllers' performance. The results show that the CSC can drive the motor with a predefined speed performance and can track a variable reference speed with an approximately zero steady state error. The results also show that the proposed position controller has the ability to effect high-precision positioning in a limited time and to track a variable reference position with a zero steady state error.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.60 no.3
• /
• pp.138-143
• /
• 2011

Electric locomotive is adapted to high speed driving and mass transportation due to obtaining high traction force. The electric locomotive is operated by motor blocks and traction motors. Train speed is controlled by suppling power from motor blocks to traction motors according to reference speed. Speed control of the electric locomotive is efficient by spending energy between motor blocks and traction motors. Currently, switched reluctance motors have been studied because the efficient is higher than induction motors. In this paper, model of the switched reluctance motor is presented and the PID controller is applied to the model for the speed control by using Simulink. Asymmetry converter is used for real-time control and system performance is demonstrated by simulating the speed of switched reluctance motor including PID controller.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.66 no.11
• /
• pp.1663-1668
• /
• 2017

A BLDC motor with higher number of phases has several advantages, compared to the conventional three-phase BLDC motors. It can reduce the commutation torque ripple and the iron loss without increasing the voltage per phase and increase the reliability and power density. Higher number of phases increase the torque-per-ampere ratio for the same machine volume and output power by widening the electrical conduction period. In this paper, the proposed seven-phase BLDC motor drive system is made into several functional modular blocks, so that it can be easily extended to other ac motor applications: back-EMF block, hysteresis current control block, pwm inverter block, phase current block, and speed/torque control block. Also in a system of BLDC motor drive, the PI controller has been widely used in the speed controller because of the simple implementation. To obtain a good speed response in a general drive system using the PI controller, the high bandwidth of a controller is established. therefore, in this paper, a Fuzzy controller is applied to the 7-phase BLDC motor drive system in order to improve the speed control performance. The Fuzzy controller is compared with a conventional PI controller through the experiment with respect to speed dynamic responses. These experimental results show that the Fuzzy controller of the 7-phase BLDC motor drive system is superior over the conventional PI controller. The algorithm using the Fuzzy controller can improve a comfortable ride in the field of high performance 7-phase BLDC motor drive applications.

• Journal of Power Electronics
• /
• v.12 no.2
• /
• pp.305-316
• /
• 2012

The paper presents an accurate loss model based controller of an induction motor to calculate the optimal air gap flux. The model includes copper losses, iron losses, harmonic losses, friction and windage losses, and stray losses. These losses are represented as a function of the air gap flux. By using the calculated optimal air gap flux compared with rated flux for speed sensorless indirect vector controlled induction motor, an improvement in motor efficiency is achieved. The motor speed performance is improved using a fuzzy logic speed controller instead of a PI controller. The fuzzy logic speed controller was simulated using the fuzzy control interface block of MATLAB/SIMULINK program. The control algorithm is experimentally tested within a PC under RTAI-Linux. The simulation and experimental results show the improvement in motor efficiency and speed performance.

• Journal of the Semiconductor & Display Technology
• /
• v.13 no.4
• /
• pp.71-76
• /
• 2014

This paper presents the implementation for the BLDC motor speed control system using VHDL and FPGA. The BLDC motor is widely used in automation for its good robustness and easy controllability. In order to control the speed of the BLDC motor, the PI controller used for static RPM output of the BLDC motor to variations in load. In addition, by using the DA converter, we were able to monitor the BLDC motor reference speed and the current speed through real time. The motor speed command and the parameters of the PI speed controller were modified easily by the FPGA and the AD converter. Finally, in order to show the feasibility of the control algorithm the speed control characteristics of the motor was monitored using an oscilloscope and the DA converter. Further, the speed control system was designed in this paper has shown the applicability of the drive system of the factory automation.

• Journal of Power Electronics
• /
• v.4 no.4
• /
• pp.217-227
• /
• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.9 no.5
• /
• pp.463-471
• /
• 1999

This paper presents a vector controlled induction motor is implemented by neural networks system compared with PI controller for the speed control. The design employed the training strategy with Neural Network Controller(NNC) and Neural Network Emulator(NNE) for speed. In order to update the weights of the controller First of all Emulator updates its parameters by identifying the motor input and output next it supplies the error path to the output stage of the controller using backpropagation algorithm, As Controller produces an adequate output to the system due to neural networks learning capability Vector controlled induction motor characteristics actual motor speed with based on neural network system follows the reference speed better than that of linear PI speed controller.