• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1954-1955
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• 2007

This paper presents a modeling method of speed controller for DC motor drive system by using the Embedded Target for TI C2000 DSP in MATLAB/SIMULINK. Speed controller is easily designed and implemented by using the MATLAB/SIMULINK program, and speed control response and stability of the DC motor can be improved. Feedback of motor speed is processed through C28x QEP(Quadrature Encoder Pulse) from encoder pulse. The controller is designed as PI speed controller. Simulation program is drawn using SIMULINK. Then a real-time program for speed control of the DC motor is downloaded into the eZdsp F2811 control board. Speed control response is verified through simulations and experiments.

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.2
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• pp.54-60
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• 2007

In this paper, we suggest the high efficient control method based on general PI control law for a variable speed refrigeration system. In the variable speed refrigeration system, the capacity and the superheat are mainly controlled by an inverter and an electronic expansion valve, respectively, for saving energy and improving coefficient of performance. Thus, we proposed a decoupling model to eliminate the interfering loop between the capacity and superheat at first. Next, we designed PI controller to control the capacity and superheat independently and simultaneously. Finally, the control performance was investigated through some experiments. The experimental results showed that the proposed PI controller based on the decoupling model can obtain good control performance under the various control references and thermal load.

• Proceedings of the KIEE Conference
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• 2001.04a
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• pp.281-284
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• 2001

This paper presents implementation of digitally speed sensorless control system for induction motor with a direct torque control(DTC) using 32bit DSP TMS320C31. The system are closed loop stator flux and torque observer for wide speed range that inputs are currents and voltages sensing of motor terminal, MRAS with rotor flux linkages for the speed turning signal, two hysteresis controllers, optimal switching look-up table and IGBT voltage source inverter. There are suggested a control algorithm and system, and given simulation and implementation results on the 2.2Kw general purposed induction motor.

• Journal of Advanced Marine Engineering and Technology
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• v.21 no.1
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• pp.82-87
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• 1997

This paper presents a method about the modeling of the medium - small diesel engine for the speed control and designs the robust speed control system by the $\mu$-synthesis, which has good performance, in spite of the existence of model uncertainities and the external disturbance. We confirmed the validity of the proposed modeling method and the designed control system by $\mu$-synthesis through the experimental responses.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.70-77
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• 2010

This paper presents the current and speed controller design procedure and their performance for the IPMSM based next generation high speed railway traction system. The next generation high speed railway system is a power distributed type and uses vector control method for a motor speed control. Since the speed and current controller gains of the vector control system directly affects to the transient characteristics and speed control capability, the systematic design of the controllers are required. In this paper the controllers are designed using the IPMSM based next generation high speed railway system parameters. Simulation programs based on Matlab/Simulink is developed. Finally the controller characteristics are analyzed by the simulation results.

• 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 Power System Engineering
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• v.3 no.2
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• pp.70-78
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• 1999

The vector controlled induction motor(I.M) with speed sensor has been widely used for variable speed drive systems. In these application fileds, speed sensorless control are expected strongly to progress reliability, simplicity and cost performance of I.M and to expand its application part. This paper describes a novel speed sensorless control method of I.M based on feedforward quick torque response control technique. Especially, this paper aimed at the realization of sensorless control in the very low speed region, The proposed method can be formulated simply from a motor circuit equation and conducted easily by detecting primary motor currents and a voltage command at every sampling time. Throughout some results of numerical simulations with the assumption of using a pulse width modulation(PWM) voltage source inverter, the validity of the method was successfully confirmed.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.175-186
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• 2021

We have studied the speed regulation of the permanent magnet synchronous motor (PMSM) servo system in this paper. To optimize the PMSM servo system's speed-control performance with disturbances, a non-linear speed-control technique using a back-propagation neural network (BP-NN) algorithm forthe controller design of the PMSM speed loop is introduced. To solve the slow convergence speed and easy to fall into the local minimum problem of BP-NN, we develope an improved BP-NN control algorithm by limiting the range of neural network outputs of the proportional coefficient Kp, integral coefficient Ki of the controller, and add adaptive gain factor β, that is the internal gain correction ratio. Compared with the conventional PI control method, our improved BP-NN control algorithm makes the settling time faster without static error, overshoot or oscillation. Simulation comparisons have been made for our improved BP-NN control method and the conventional PI control method to verify the proposed method's effectiveness.

• Journal of Power Electronics
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• v.15 no.1
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• pp.246-255
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• 2015

This paper presents experimental results and its assessment of a variable-speed wind power generation system (VSWPGS) using permanent magnet synchronous generator (PMSG) and boost chopper circuit (BCC). Experimental results are obtained by a test bench with a wind turbine emulator (WTE). WTE reproduces the behaviors of a windmill by using servo motor drives. The mechanical torque references to drive the servo motor are calculated from the windmill wing profile, wind velocity, and windmill rotational speed. VSWPGS using PMSG and BCC has three speed control modes for the level of wind velocity to control the rotational speed of the wind turbine. The control mode for low wind velocity regulates an armature current of generator with BCC. The control mode for middle wind velocity regulates a DC link voltage with a vector-controlled inverter. The control mode for high wind velocity regulates a pitch angle of the wind turbine with a pitch angle control system. The hybrid of three control modes extends the variable-speed range. BCC simplifies the maintenance of VSWPGS while improving reliability. In addition, VSWPGS using PMSG and BCC saves cost compared with VSWPGS using a PWM converter.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.483-485
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• 1999

Recently, distributed control network system has been widely applied to on-board control system than conventional relay logic with control wire. This paper presents two configuration of driver's desk system using TCN(Train Communication Network). One is configured with TCN, the other is partial adoption of TCN.