• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.152-163
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• 2004

This paper presents a sensorless speed control of cylindrical permanent magnet synchronous motors(PMSM) using an adaptive integral binary observer In view of composition with a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. However, the steady state estimation accuracy and robustness are dependent upon the width of the constant boundary. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. With the help of integral characteristic, the rotor speed can be finely estimated and utilized for a sensorless speed controller for PMSM. Since the Parameters of the dynamic equations such as machine inertia or a viscosity friction coefficient are lot well known, there are many restrictions in the actual implementation. The proposed adaptive integral binary observer applies an adaptive scheme so that observer may overcome the problem caused by using the dynamic equations and the rotor speed is constructed by using the Lyapunov function. The observer structure and its design method are described. The experimental results of the proposed algorithm are presented to demonstrate the effectiveness of the approach.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.773-778
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• 2001

This paper describes the implementation of the vector control schemes for a variable-speed 131kW PMSM (Permanent Magnet Synchronous Motor) in super-high speed application. The vector control with synchronous reference frame current regulator has been implemented with the challenging requirements such as the extremely low stator inductance$(28^{\mu}H)$, the high dc link voltage(600V) and the high excitation frequency(1.2kHz). Because the conventional position sensor is not reliable in super-high speed, a vector control scheme without any position sensor has been proposed. The proposed sensorless algorithm is implemented by processing the output voltage of the PI current regulator, and hence the structure is simple and the estimated speed is robust to the measurement noise. The experimental system has been built and the proposed control has been implemented and evaluated. The test result, up to the speed of 60,000 r/min, shows the validity of the proposed control.

• Proceedings of the KIPE Conference
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• 2001.10a
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• pp.355-359
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• 2001

This paper presents an implementation of digital control system of speed sensorless for Reluctance Synchronous Motor (RSM) drives with DTC. The control system consists of stator flux observer, rotor position/speed/torque estimator, two hysteresis band controllers, an optimal switching look-up table, IGBT voltage source inverter, and TMS320C31 DSP controller by using fully integrated control software. The stator flux observer is based on the combined voltage and current model with stator flux feedback adaptive control that inputs are current and voltage sensing of motor terminal with estimated rotor angle for wide speed range. The rotor position is estimated by observed stator flux-linkage space vector. The estimated rotor speed is determined by differentiation of the rotor position used only in the current model part of the flux observer for a low speed operating area. It does not require the knowledge of any motor parameters, nor particular care for motor starting, In order to prove the suggested control algorithm, we have a simulation and testing at actual experimental system. The developed sensorless control system is shown a good speed control response characteristic results and high performance features in 50/1000 rpm with 1.0Kw RSM having 2.57 ratio of d/q reluctance.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.56-65
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• 1998

In this paper, a neural network(NN) control system is proposed and practically implemented, which is adequate to the induction motor speed control system with frequent load variation. The back propagation neural network technique is used to provide a real adaptive estimation of the motor parameter. The error between the desired state variable and the actual one is back-propagated to adjust the motor parameter, so that the actual state variable will coincide with the desired one. Designed control system is based on PC-DSP structure for the purposed of easiness of applying NN algorithm. Through computer simulation and experimental results, it is verified that proposed control system is robust to the load variation and practical implementation is possible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.63-70
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• 2003

In this paper, an MFC (Mass Flow Controller) which is widely used in many semiconductor manufacturing processes for controlling the mass flow rate of a gas is designed and implemented using the PIC 16F876 of Microchip, Inc. The MFC implemented in this thesis has the form of hybrid-type, i.e., the mixed-type of the analog-type MFC, which has many problems such as low accurary, and digital-type MFC, which use an expensive DSP (Digital Signal Processor) and an ADC (Analog to Digital Convertor) with high precision. The MFC is consists of the sensor unit, the control unit and the actuator unit, and it has used the automatic calibration algorithm and the reference table method for the improvement of the performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.376-379
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• 2000

In this paper, this system makes use of the analog infrered rays sensor and converts the feature of fish analog signal when sensor is operating with CPU(80C196KC). Then, After signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error backpropagation is used as a learning algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long time when random initial weights are used, off-line learning is induced to decrease the progress time. We confirmed this method has better performance than somewhat outdated machines.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.05a
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• pp.10-13
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• 2002

In this study, we used a 16-bit microprocessor, 80C196KC for a control part in order to develop a multi-functional wheel-chair system, and implemented a joy-stick to control this system. For the complete system, we used a commercial electromotive wheelchair as a basic plant, and applied an encoder to get the rotating number of the motor to transfer data to the MCU to control the motor. We used PWM (Pulse Width Modulation) method to control the wheel-chair motor where a H-bridge circuit was configured. We used the fuzzy control algorithm for the operation of DC motor, which was attached to the electromotive wheelchair and manipulated following the change of the joystick position while a user was controlling the Joystick. He also could control the speed and direction of DC motor as well as control position information.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.280-285
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• 2011

Recently, with the development of service robots and the concept of ubiquitous, the position estimation of mobile objects has received great interest. Some of the localization schemes are introduced, which provide the relative location of the moving objects subjected to accumulated errors. To implement a real time localization system, a new absolute position estimation method for a mobile robot in indoor environment is proposed. Design and implementation of the localization system comes from the usage of active beacon systems (based upon RFID technology). The active beacon system is composed of an RFID receiver and an ultra-sonic transmitter. The RFID receiver gets the synchronization signal from the mobile robot and the ultra-sonic transmitter sends out the traveling signal to be used for measuring the distance. Position of a mobile robot in a three dimensional space can be calculated basically from the distance information from three beacons and the absolute position information of the beacons themselves. In some case, the mobile robot can acquire the ultrasonic signals from only one or two beacons, due to the obstacles located along the moving path. In this paper, a position estimation scheme using fewer than three sensors is developed. Also, the extended Kalman filter algorithm is applied for the improvement of position estimation accuracy of the mobile robot.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.10
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• pp.1020-1023
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• 2011

In this paper, we present a symbol remapping method of BRGC M-ary QAM signal by using LLR soft bit decision information which is obtained after iterative decoding process. In order to reconstruct estimated transmitted signal constellation, we have to use exponential or hyperbolic tangent(tanh) function resulting in high implementation complexity. The BRGC mapping rule enables us to use a recursive operation. In addtion, we reduce the implementing complexity by using a curve fitting algorithm.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1337-1349
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• 2011

So far as a solution of the given consistent linear system is concerned many numerical methods - both mathematically non-iterative as well as iterative - have been reported in the literature over the last couple of centuries. Most of these methods consider all the equations including linearly dependent ones in the system and obtain a solution whenever it exists. Since linearly dependent equations do not add any new information to a system concerning a solution we have proposed an algorithm that identifies them and prunes them in the process of solving the system. The pruning process does not involve row/column interchanges as in the case of Gauss reduction with partial/complete pivoting. We demonstrate here that the use of pruning as an inbuilt part of our solution process reduces computational and storage complexities and also computational error.