• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.1182-1184
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• 2001

This paper presents a neural network based self-tuning fuzzy PID control scheme for induction motor speed control. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PID controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.327-331
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• 1989

This paper concerned about a study on the direct pole placement PID self-tuning controller design for Robot manipulator control system. The method of a direct pole placement self-tuning PID control for a DC motor of robot manipulator tracks a reference velocity in spite of the parameters uncertainties in nonminimum phase system. In this scheme, the parameters of controller are estimated by the recursive least square(RLS) identification algorithm, the pole placement method and diophantine equation. A series of simulation in which minimum phase system and nonminimum phase system are subjected to a pattern of system parameter changes is presented to show some of the features of the proposed control algorithm. The proposed control algorithm which shown are effective for the practical application, and experiments of DC motor speed control for Robot manipulator by a microcomputer IRH-PC/AT are performed and the results are well suited.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.559-564
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• 2001

In order to apply into a compact and reliable centrifugal blood pump, this paper introduces a self-bearing motor in which a rotor is rotated without contact. The rotor is actively controlled in only radial directions, while the axial and tilting motions are passively stable owing to the disk-shape structure of the rotor. A prototype was made in outer-rotor type that is far better in the compactness than inner-rotor type. The prototype could be driven up to 8000 rpm with the rotor vibration under 0.12mm. The maximum cardiac output and pressure head were 9 L/min and over 200 mmHg, respectively. These experimental results show that the proposed self-bearing motor has sufficient performance for application to a real blood pump.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.852-857
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• 2004

In this paper, an angular self-sensing algorithm is proposed and implemented to a Lorentz force type integrated motor-bearing system. It is based on the principle that the flux linkages of stator windings, calculated from the voltage and torque control current, are the functions of the rotor angle. The tracking angular position error is proven to vanish using the Lyapunov stability method, and the experimental results show that the initial error decays within about 5 seconds. It is found that the resolution of the algorithm remains about 1º over the speed range of 100 to 1000 rpm.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.249-255
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• 2000

The design and test of an magnetostrictive linear motor(MLM) that operates based on self-moving cell concept is presented. The moving cell is composed of Terfenol-D linear actuator and a ring structure, and a cell train is constructed by connecting two cells in series. Since this motor uses the stroke of Terfenol-D actuators and friction force of the cells, it can essentially produce long stroke and large force. The overall performance of the MLM was measured in terms of speed and force. The pushing force is directly related with the friction force. This work is a proof-of-concept stage and investigation is necessary for realistic application.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.1-67
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• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.3
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• pp.173-183
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• 1998

In this paper, an auto-tuning method for fuzzy controller's membership functions based on the neural network is presented. The neural network emulator offers the path which reforms the fuzzy controller's membership functions and fuzzy rule, and the reformed fuzzy controller uses for speed control of induction motor. Thus, in the case of motor parameter variation, the proposed method is superior to a conventional method in the respect of operation time and system performance. 32bit micro-processor DSP(TMS320C31) is used to achieve the high speed calculation of the space voltage vector PWM and to build the self-learning fuzzy control algorithm. Through computer simulation and experimental results, it is confirmed that the proposed method can provide more improved control performance than that PI controller and conventional fuzzy controller.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.1
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• pp.93-100
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• 2017

Four-stroke cycles in an automobile engine are suction stroke, compression stroke, combustion stroke and exhaustion stroke. A normal operation of engine in compression and power stroke must be processed in optimal fuel-air pressure. In this paper we describe a development of measuring equipment for engine cylinder pressure with observing supply current to self motor(start motor). By comparing the current wave on pressure of the 4 or 6 cylinder in engine, a abnormal cylinder state will be found. The validity of the proposed measuring equipment was shown by experiment for real automobile.

• Proceedings of the KIEE Conference
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• 2005.10a
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• pp.136-138
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• 2005

The conventional self-tuning methods have the speed control problem of nonlinear BLDC motor which can't adapt against any kinds of noise or operation circumstances. In this paper, supposed to solve these problem to PI parameters controller algorithm using ANN. In the proposed algorithm, the parameters of the controller were adjusted to reduce by on-line system the error of the speed of BLDC motor. In this process, EBPA NN was constituted to an output error value of a BLDC motor and conspired an input and output. The performance of the self-tuning controller is compared with that of the PI controller tuned by conventional method(Z&N). The effectiveness of the proposed control method IS verified thought the Matlab Simulink.

• Proceedings of the KIEE Conference
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• 1990.11a
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• pp.319-322
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• 1990

Self-controlled permanent magnet synchronous motor (PMSM) has similar operating characteristics as seperately excited dc motor. It is favored in servo applications due to its improvement of efficiency and maintenance. This paper presents completely digitalized controller using microprocessor and voltage fed inverter. The speed control system for PMSM is implemented. To control the motor speed, the control system regulates the magnitude of Inverter output voltage by regular-sampled PWM method to generate sinusoidal PWM wave with microprocessor. And to keep the range of inverter switching frequency, it varies the number of pulse train according to the speed.