• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1509-1512
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• 2003

The electric power wheelchair needs to control motor torque and speed for responding to variable actions given by handling a joystick. In this paper a DSP-based BLDC motor controller using a single dc-link current sensor is presented for electric power wheelchair. It is composed by a DSP processor and three-phase inverter module. To control torque, high speed current control is achieved by the PI controller and pulse width modulation (PWM) signals with 25 kHz carrier frequency, which is performed by 200 ${\mu}sec$ cycle. The speed controller computes the new direct current reference from the speed error and the PI control equation. The displacement value by handling the joystick is converted to reference speeds of right and left wheel motors using nonholonomic wheelchair kinematics. Experimental results show that the presented control system is enough to implement a speed servo in wheelchair driving.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.11a
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• pp.307-312
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• 2007

The paper is proposed artificial neural network(ANN) sensorless control of induction motor drive with fuzzy learning control-fuzzy neural network(FLC-FNN) controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of induction motor using FLC-FNN and estimation of speed using ANN controller The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable will coincide with the desired one. The proposed control algorithm is applied to induction motor drive system controlled FLC-FNN and ANN controller, Also, this paper is proposed the analysis results to verify the effectiveness of the FLC-FNN and ANN controller.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.12
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• pp.691-696
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• 2002

This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 2000.11b
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• pp.336-338
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• 2000

Recently many studies have been performed for variable speed control of induction motor. Direct Torque Control(DTC) is emerging technique for variable speed control of PWM inverter driven induction motor. DTC allows the direct control of stator flux and instantaneous torque through simple algorithm. In this paper ASIC design technique using VHDL is applied to DTC based speed control of induction motor. ASIC for DTC based speed control is designed through the description of coordinate transformation, speed controller stator flux and torque estimator, stator flux and torque controller, stator flux position detector. FSM(Finite State Machine) and inverter voltage switching vector. Finally the above system has been implemented on the FPGA (XC4052XL-PG411). Simulation and experiment has been performed to verify the performance of the designed ASTC.

• Proceedings of the KIPE Conference
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• 2003.07b
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• pp.532-535
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• 2003

In this paper, a Pl controlled feedback closed-loop voltage regulation scheme of the three-phase squirrel cage rotor self-excited induction generator (SEIG) driven by a variable-speed prime mover (VSPM) such as a wind turbine is designed on the basis of the static VAR compensator (SVC) and discussed in experiment fer the promising stand-alone power independent conditioner. The simulation and experimental results of the three-phase SEIG with the simple SVC controller for its stabilized voltage regulation prove the practical effectiveness of the additional SVC control loop scheme including the PI controller with fast response characteristics and steady-sate performance improvement.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.449-452
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• 1998

In this paper, we implemented the variable fuzzy speed controller of an IM(induction motor) using the fuzzy control algorithms. Specially, we proposed a self-tuning technique of scale factors which could make easily the fuzzy speed controller optimize. Comparing with the conventional PI speed controller, the dynamic performances of a proposed fuzzy controller such as the reaching time, the maximum overshoot and the robustness against load disturbance were substantially improved.

• Proceedings of the KIEE Conference
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• 2002.07b
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• pp.1172-1174
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• 2002

An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.491-494
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• 1997

In this paper, we suppose a fuzzy logic controller for cruise control of vehicle. Generally, fuzzy logic controller is known as a controller which can be coped with a non-linear and a complex system. The proposed fuzzy logic controller consists of three input variables; that is, a desired speed, a current vehicle speed, and a current acceleration, and one output variable, throttle angle. The supposed fuzzy logic controller is for engine speed control system is implemented on 80586 microprocessor with DT-2801.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.1
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• pp.111-119
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• 2013

This paper present stabilization control of fixed speed wind generator by using variable speed permanent magnet wind generator in a wind farm connected with multi-machine power system. A novel direct-current based d-q vector control technique of back to back converter integrated with Fuzzy Logic Controller for optimal control configuration is proposed, in which both active and reactive powers delivered to a power grid system are controlled effectively. Simulation analyses have been performed using PSCAD/EMTDC. Simulation results show that the proposed control scheme is very effective to enhance the voltage stability of the wind farm during fault condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5416-5426
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• 2012

This study uses the algorithm which estimates the magnetic flux using different models in the low speed driving area and the high speed driving area by the voltage-current model synthesis magnetic flux Estimator and, from this result, estimates the magnetic flux angle to achieve the stable speed control through all the areas from the low speed to the high speed drive. In particular, the current change and the magnetic flux change under variable load were estimated in real time in the low speed area and this made the control characteristic improved in the low speed area. According to this, even under variable load, the more stable simulation and experiment could have been completed using PI current controller and PI flux controller in all the areas. As a result, the outstanding speed control characteristic has been achieved.