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

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.6
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• pp.33-39
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• 2007

In this paper, novel topology for fast response of various loads is proposed. The windup phenomenon appears and results in performance degradation when the PI controller output is saturated. A new anti-windup PI controller is proposed to improve the control performance of variable speed motor drives, and it is experimentally applied to the speed control of a hysteresis current-controlled SRM driven by an asymmetry bridge converter. The experimental results show that the speed response has much improved performance, such as small overshoot and fast settling time, over the conventional PI control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.2
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• pp.231-239
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• 1998

In this paper, we designed a current controlling servo system for speed control of a PMSM. In existing auto-tuning methods for PI controller parameters, the output response is delayed and the overshoot is generated. By solving these existing problems in this paper, a new PI auto-tuning method is applied to the speed controller for fast-response and reduced overshoot. PMSM servo systems offer a great advantage in unmanned factories where a great number of servo motors are employed, because of its easy maintenance characteristics and controllability. The implemented servo system is composed of absolute position detecting circuits of a rotor, a new auto-tuning PI control algorithm, a speed controller by using DSP, and power driving section. The proposed servo system is verified for it's practical availability by considering experimental results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.2
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• pp.157-165
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• 2002

This paper presents the implementation of the speed control system for 3 phase induction motor using PD controller and neural networks. The PD controller is used to control the motor and to train neural networks at the first time. And neural networks are widely used as controllers because of a nonlinear mapping capability, we used feedforward neural networks(FNN) in order to simply design the speed control system of the 3 phase induction motor. Neural networks are tuned online using the speed reference, actual speed measured from an encoder and control input current to motor. PD controller and neural networks are applied to the speed control system for 3 phase induction motor, are compared with PI controller through computer simulation and experiment respectively. The results are illustrated that the output of the PD controller is decreased and feedforward neural networks act main controller, and the proposed hybrid controllers show better performance than the PI controller in abrupt load variation and the precise control is possible because the steady state error can be minimized by training neural networks.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.6
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• pp.602-611
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• 2004

Servo system has commonly adapted PI controller with fixed gains, because of its simplicity and determinative relationship among the parameters. The fixed gains PI system may be applied well to some operation conditions, but not non-linearities, complex and time variant operation conditions. For solving these problems, another conventional method, 'variable gun schedule according to speed', is published. The value of gain is determined according to the absolute value of the mover real speed. In this paper, FSTPIC(Fuzzy Self-Tuning PI Controller) is proposed based on various experiences to rapidly reduce speed error and to secure a good speed response characteristics. The effectiveness of proposed algorithms is demonstrated by comparing to two conventional gain systems via 4-quadrant operation.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.11
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• pp.664-670
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• 2004

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 that 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 zero. For zero and low speed operation, PI controller gains of rotor position tracking controller have a variable structure according to the estimated rotor velocity. In order to boost the bandwidth of PI controller around zero speed, a loop recovery technique is applied to the control system. The proposed method only requires the flux linkage of permanent magnet and is insensitive to the parameter estimation error and variation. The designers can easily determine the possible operating range with a desired bandwidth and perform the vector control even at low speeds. The experimental results show the satisfactory operation of the proposed sensorless algorithm under rated load conditions.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.438-445
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• 2022

Blade efficiency decreases when the rotor speed is kept constant even though the wind speed is higher than the rated value. Therefore, a speed controller is used to regulate the rotor speed in the high-wind-speed region. In stall-blade wind turbine, the role of the speed controller is important because precise aerodynamic regulation is unavailable. In this study, an effective parameter design method of a PI speed controller is proposed to limit the speed overshoot of a type 4 wind turbine with stall blades even though wind gust occurs. The proposed method considers the efficiency characteristics of the stall blade and the mechanical inertia of the wind turbine rotor. It determines the bandwidth of the speed controller to comply with the speed limit during generator speed overshoot for the worst case of wind gust. The proposed method is verified through intensive simulations with a MATLAB/SIMULINK model and experimental results obtained using a 3 kW MG set of wind turbine simulator.

• Proceedings of the KIEE Conference
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• 2006.04b
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• pp.176-178
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• 2006

This paper is intended to research the speed response of switched reluctance motor (SRM) using sliding mode control method when load is changing. The simulation compare only control by PI controller with control by PI controller and sliding mode controller. It compare with speed response using MATLAB/SIMULINK.

• Journal of Power Electronics
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• v.10 no.1
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• pp.65-71
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• 2010

This paper presents the design and implementation of voltage source inverter type SVPWM based speed control of an induction motor using a fuzzy PI controller. This scheme enables us to adjust the speed of the motor by controlling the frequency and amplitude of the stator voltage; the ratio of the stator voltage to the frequency should be kept constant. A model of the fuzzy control system is implemented in real time with a Xilinx FPGA XC3S 400E. It is introduced to maintain a constant speed to when the load varies.