• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.473-479
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• 2016

This paper describes an accurate and stable current control method of switched reluctance motors(SRMs), which have recently attracted considerable wide attention owing to their favorable features, such as high performance, high durability, structural simplicity, low cost, etc. In most cases, the PI controllers(PICC) have been used mostly for the current control of electric motors because their algorithm and selection of controller gain are relatively simpler compared to other controllers. On the other hand, the PI controller requires an adjustment of the controller gains for each operating point when nonlinear system parameters change rapidly. This paper presents a stable current control method of an SRM using self-tuning fuzzy current controller(STFCC) under nonlinear parameter variation. The performance of the considered method is validated via a dynamic simulation of the current controlled SRM drive using Matlab/Simulink program.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.434-440
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• 2023

This paper propose the method that measure the main system parameters for current control of a.c. motor adopting the vector control technique. The automatical method that tuning PI control gains for current control of servo motors are used frequently through the information of main system parameters, wire resistance and inductance. In this study, the techniques to measure these two system parameters through the control of 3-phase inverter are presented. These control and measuring method are implemented by measuring output phase current obtained as a results of the step current control using simple proportional feedback input. Moreover, this method use freewheeling current of inverter at special switching mode for measuring inductance. This analytic strategy is could measure and calculate the system parameters without the complex measurement algorithm and new additional measuring circuits. That is could measure the total resistance and total inductance including wiring resistance and conduction resistance of switching devices using real driving circuits to control the motors.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.189-195
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• 2005

This paper presents a new velocity estimation strategy for a non-salient permanent magnet synchronous motor drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system, which contains the rotor position error information. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error at zero. For zero and low speed operation, the PI gain of the rotor position tracking controller has a variable structure according to the estimated rotor velocity. Then, at zero speed, the rotor position and velocity have sluggish dynamics because the varying gains are very low in this region. In order to boost the bandwidth of the PI controller during zero speed, the loop recovery technique is applied to the control system. The PI tuning formulas are also derived by analyzing this control system by frequency domain specifications such as phase margin and bandwidth assignment.

• Proceedings of the KIEE Conference
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• 2008.04c
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• pp.128-130
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• 2008

This paper presents an algorithm to design a self-tuning proportional-integral(PI) speed controller for servo systems. The control gains are calculated with estimated system parameters, i.e. inertia and viscous damping which are estimated by initial operation. The simulation and experimental results show the feasibility and performance of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 2003.04a
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• pp.176-178
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• 2003

This paper presents a new velocity estimation strategy of a non-salient permanent magnet synchronous motor(PMSM) drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system which has the information of rotor position error. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error to aero. For zero and low speed operation, the PI gains of rotor position tracking controller have a variable structure. The PI tuning formulas are derived by analyzing this control system using the frequency domain specifications such as phase margin and bandwidth assignment.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.219-225
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• 1991

The characteristics of a power plant changes as it operates for a long time and/or for different operating points. As a result, operators must retune gains of the controllers for better performance. In fact, skilled operators can retune the gains in reference to recorded data obtained by a test called dynamic test. The dynamic test, however, requires much time, and can be heavy burden for operators. In this paper, an expert knowledge-based auto-tuner is designed for drum-type boiler controllers of a fossil power plant using fuzzy logic. The performance of the proposed auto-tuner is shown via computer simulation and the simulation results show that the proposed auto-tuner is satisfactory for the desired performance.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2120-2122
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• 2002

There are several types of control systems that use fuzzy logic controller as a essential system component. The majority of research work on fuzzy PID controller focuses on the conventional two-input PI or PD type controller. However, fuzzy PID controller design is a complex task due to the involvement of a large number of parameters in defining the fuzzy rule base. In this paper we combined conventional PI type and PD type fuzzy controller and set the initial parameters of this controller from the conventional PID controller gains obtained by Ziegler-Nichols tuning or other coarse tuning methods. After that, by replacing some of these parameters with sing1e neurons and making them to be adjusted by back-propagation learning algorithm we designed a neuro-fuzzy controller which showed good performance characteristics in both computer simulation and actual application.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.3B no.2
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• pp.97-102
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• 2003

In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.265-271
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• 1999

In the feed drive systems or the spindle systems of machine tools that consist of many mechanical components, a torsional vibration is often generated because of its elastic elements in torque transmission-Generally, the accuracy of motion control system is strongly influenced by the dynamic behavior of coupled transmission components Especially, a torsional vibration caused by the elasticity of mechanical elements might deteriorate the quick movement of system and lead to shorten the life time of the mechanical transmission elements. So, it is necessary to analyze the electromechanical system mathematically to optimize the dynamic characteristics of the feed m1d spindle system. In this paper, based on the DC motor model, a model of electro-drive system with motor has been developed and an optimal criterion for tuning the gain of speed controller is discussed. The frequency bandwidth of the system and the damping ratio in time domain are optimal design specifications for the gain adjustment speed controller. The gains of PI speed controller are then derived from the bandwidth and damping ratio, and those relationships have been classified.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1453-1455
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• 2005

This paper presents self tuning PI controller of IPMSM drive using neural network. Self tuning PI controller is developed to minimize overshoot, rise time and settling time following sudden parameter changes such as speed, load torque and inertia. Also, this paper is proposed speed control of IPMSM using neural network and estimation of speed using artificial neural network(ANN) controller. The results on a speed controller of IPMSM are presented to show the effectiveness of the proposed gain tuner. And this controller is better than the fixed gains one in terms of robustness, even under great variations of operating conditions and load disturbance.