• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.867-872
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• 2022

The effect of load is an important factor in precise speed control of a motor. n this study, we design a state observer that can estimate and define one state of disturbance including errors and nonlinear terms of mathematical models, which is not easy with a mathematical model. Then, the observation gain is set so that the estimation error of the state observation converges to 0, and the estimated state is used in the back stepping controller to design a controller capable of precise speed tracking. As a result of applying to 1 [hw] class Interior Permanent Magnet Synchronous Motor, excellent stste variable observation and tracking performance can be confirmed.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.5
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• pp.349-356
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• 2021

Permanent magnet synchronous motors are mainly used in the traction of electric vehicle and home application products including air-conditioners and refrigerators. For sensorless control without rotor position sensors, I-F control is applied for initial starting at low speeds, and mode is changed to sensorless control when the rotor speed is sufficiently accelerated for estimating rotor position. When the mode is changed to the sensorless control from the open-loop starting, the initial integral value of the speed controller should be considered by load condition; otherwise, the transition to sensorless control may fail. The sensorless transfer algorithm of PM synchronous motor based on load condition for smooth transition is proposed. The performance of the proposed sensorless transfer algorithm was verified by experiments.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.6
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• pp.1215-1224
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• 2011

Recently, a lot of research for the smart grid technology have been carried out to achieve energy efficiency for the electronic products. In order to practically apply this study, smart instruments which are capable of the AMI (Advanced Metering Infrastructure) and DR (Demand Response) function are necessary. However, it is difficult to apply the function of the smart grid to the electronic product that cannot support the smart grid. Accordingly, the efficient use of electric energy is impossible. In order to solve this problem, the electronic product has to be changed into the exclusive electronic product supporting smart grid technology or the smart controller has to be attached the outside of the device. In this study, we developed the smart controller for connecting the electric appliances to the smart grid system. It can be attached to the illumination and the smart grid-based lamp control system at home. We additionally designed the message frame and the protocol to operate the smart controller with the AMI based EMS (Energy Management Server). We developed an experimental system to practically verify functions of the smart controller which is attached to the lighting device. From the system, we showed that the electric source of the illumination can be controlled according to the load change and saved energy effectively. We also confirmed the structural benefit and the energy-efficient effect through the verification of the smart controller.

• Proceedings of the KIPE Conference
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• 2001.07a
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• pp.417-421
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• 2001

In this paper, a novel design method of variable motor inetia in Induction motor drive system is proposed. The inertia of a load and a motor are estimated by using RLS (Recursive Least Square) algorithm. The speed controller is designed by Kharitonove theory of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• Journal of Power Electronics
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• v.8 no.4
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• pp.354-362
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• 2008

This paper presents neural load torque compensation method which is composed of a deadbeat load torque observer and gains compensation by a parameter estimator. As a result, the response of the PMSM (permanent magnet synchronous motor) obtains better precision position control. To reduce the noise effect, the post-filter is implemented by a MA (moving average) process. The parameter compensator with an RLSM (recursive least square method) parameter estimator is adopted to increase the performance of the load torque observer and main controller. The parameter estimator is combined with a high performance neural load torque observer to resolve problems. The neural network is trained in online phases and it is composed by a feed forward recall and error back-propagation training. During normal operation, the input-output response is sampled and the weighting value is trained multi-times by the error back-propagation method at each sample period to accommodate the possible variations in the parameters or load torque. As a result, the proposed control system has a robust and precise system against load torque and parameter variation. Stability and usefulness are verified by computer simulation and experiment.

• Journal of Power Electronics
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• v.12 no.6
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• pp.904-911
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• 2012

This paper presents a fuzzy adaptive speed controller that guarantees a fast dynamic behavior and a precise trajectory tracking capability for surfaced-mounted permanent magnet synchronous motors (SPMSMs). The proposed fuzzy adaptive control strategy is simple and easy to implement. In addition, the proposed speed controller is very robust to system parameter and load torque variations because it does not require any accurate parameter values. The global stability of the proposed control system is analytically verified. To evaluate the proposed fuzzy adaptive speed controller, both simulation and experimental results are shown under motor parameter and load torque variations on a prototype SPMSM drive system.

• Journal of Electrical Engineering and Technology
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• v.5 no.4
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• pp.552-560
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• 2010

This paper presents an application of layered Artificial Neural Network controller to study load frequency control problem in power system. The objective of control scheme guarantees that steady state error of frequencies and inadvertent interchange of tie-lines are maintained in a given tolerance limitation. The proposed controller has been designed for a two-area interconnected power system. Only one artificial neural network controller (ANN), which controls the inputs of each area in the power system together, is considered. In this study, back propagation-through time algorithm is used as neural network learning rule. The performance of the power system is simulated by using conventional integral controller and ANN controller, separately. For the first time comparative study has been carried out between SMES and CES unit, all of the areas are included with SMES and CES unit separately. By comparing the results for both cases, the performance of ANN controller with CES unit is found to be better than conventional controllers with SMES, CES and ANN with SMES.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.308-313
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• 2022

This paper proposes a velocity control method for a permanent magnet synchronous motor (PMSM) based on the Koopman operator that does not require model parameter information except for pole-pair of the motor and external load. First, the Koopman operator is derived using observable functions and observation data. Then, the desired q-axis current corresponding to the desired velocity is generated using the relationship between the continuous-time Koopman operator and the dynamics of PMSM. Also, the dynamic equation of PMSM is expressed as a linear form in observable space using the discrete-time Koopman operator. Finally, it is applied to the linear quadratic regulator (LQR) to derive the final form of control input. To verify the proposed method, the conventional cascade PI controller and the LQR controller configured with the existing technique are compared with the proposed method in the viewpoint of q-axis current generation and velocity tracking performance in an environment with noise and external load.

• Transactions on Electrical and Electronic Materials
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• v.18 no.3
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• pp.129-135
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• 2017

This paper introduces a design and a simulation of a hybrid active power filter (HAPF) for harmonics reduction given an ideal supply source. The synchronous reference frame method has been used here to identify the reference currents. The proposed HAPF uses a new artificial- intelligence technique called Particle Swarm Optimization (PSO) for tuning the parameters of a proportional and integral controller called PI-PSO. The PI-PSO controller is used to archive optimality for the DC-link voltage of the HAPF-inverter. The hysteresis non-linear current control method is used in this approach to compare the extracted reference and the actual currents in order to generate the pulse gate required for the HAPF. Results obtained by simulations with Matlab/Simuling show that the proposed approach is very flexible and effective for eliminating harmonic currents generated by the non-linear load with the HAPF based PSO tuning.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1423-1433
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• 2018

Recently, a permanent magnet synchronous motor of middle and small-capacity has high torque, high precision control and acceleration / deceleration characteristics. But existing control has several problems that include unpredictable disturbances and parameter changes in the high accuracy and rigidity control industry or nonlinear dynamic characteristics not considered in the driving part. In addition, in the drive method for the control of low-vibration and high-precision, the process of connecting the permanent magnet synchronous motor and the load may cause the response characteristic of the system to become very unstable, to cause vibration, and to overload the system. In order to solve these problems, various studies such as adaptive control, optimal control, robust control and artificial neural network have been actively conducted. In this paper, an incremental encoder of the permanent magnet synchronous motor is used to detect the position of the rotor. And the position of the detected rotor is used for low vibration and high precision position control. As the controller, we propose augmented state feedback control with a speed observer and first order deadbeat disturbance observer. The augmented state feedback controller performs control that the position of the rotor reaches the reference position quickly and precisely. The addition of the speed observer to this augmented state feedback controller compensates for the drop in speed response characteristics by using the previously calculated speed value for the control. The first order deadbeat disturbance observer performs control to reduce the vibration of the motor by compensating for the vibrating component or disturbance that the mechanism has. Since the deadbeat disturbance observer has a characteristic of being vulnerable to noise, it is supplemented by moving average filter method to reduce the influence of the noise. Thus, the new controller with the first order deadbeat disturbance observer can perform more robustness and precise the position control for the influence of large inertial load and natural frequency. The simulation stability and efficiency has been obtained through C language and Matlab Simulink. In addition, the experiment of actual 2.5[kW] permanent magnet synchronous motor was verified.