• Journal of Power Electronics
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• v.15 no.1
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• pp.177-189
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• 2015

The output of the controller is said to exceed the input limits of the plant being controlled when a control system operates in a non-linear region. This process is called the windup phenomenon. The windup phenomenon is not preferable in the control system because it leads to performance degradation, such as overshoot and system instability. Many anti-windup strategies involve switching, where the integral component differently operates between the linear and the non-linear states. The range of state for the non-overshoot performance is better illustrated by the boundary integral error plane than the proportional-integral (PI) plane in windup inspection. This study proposes a PI controller with a separate closed-loop integral controller and reference value set with respect to the input command and external torque. The PI controller is compared with existing conventional proportional integral, conditional integration, tracking back calculation, and integral state prediction schemes by using ScicosLab simulations. The controller is also experimentally verified on a direct current motor under no-load and loading conditions. The proposed controller shows a promising potential with its ability to eliminate overshoot with short settling time using the decoupling mode in both conditions.

• Journal of Power Electronics
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• v.12 no.6
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• pp.1003-1010
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• 2012

Recent power electronics and variable-frequency motor drive technologies have been applied to air conditioners to improve efficiency and power density. However, the mechanical vibrations and acoustic noise resulting from the compressor still remain as a serious problem. This paper presents the development and implementation of an online disturbance state-filter for the suppression of multiple unknown and time-varying vibrations of air conditioning systems. The proposed design has a form of the state-filter based on a Luenburger-style closed-loop speed observer. An active vibration decoupling strategy with an estimated disturbance is provided, which manipulates a motor torque command. Since the proposed estimation does not require any additional transducers or hardware for obtaining real-time information upon disturbances, it is suitable for retrofitting industrial air conditioners.

• Proceedings of the KIEE Conference
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• 2009.04b
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• pp.225-227
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed artificial intelligent-PI(AIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.10
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• pp.949-958
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• 2012

Position tracking control of a link of a slave manipulator which needed to track the corresponding link of a master manipulator was addressed in this paper. Since driving torque from motor is transmitted through a set of flexible cable to link, the motion control system is modeled by a two-mass model connected with elastic coupling which has finite stiffness. Relative vibration of two-mass resonant system is a serious problem to operate manipulator. This paper proposed sliding mode control to reduce resonant vibration and fine position tracking control. Also, a pseudo-sliding mode control which uses a saturation function instead of a signum function was discussed and showed that the pseudo-sliding mode control can improve disturbance regulation performance as well as guarantees fine command tracking without chattering which is an inherent drawback of basic sliding mode control. In addition, a disturbance observer based sliding mode control has been suggested to improve disturbance regulation performance. The feasibility of the proposed control design was verified along with some simulation results.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.369-372
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• 2002

In this research, a vision system for detecting tool breakage which is hardly detected by such indirect in-process measurement method as acoustic emission, cutting torque and motor current was developed and embedded into a PC-NC system. The vision system consists of CMOS image sensors, a slit beam laser generator and an image grabber board. Slit beam laser was emitted on the tool surface to separate the tool geometry well from the various obstacles surrounding the tool. An image of tool is captured through two steps of signal processing, that is, median filtering and thresholding and then the tool is estimated normal or broken by use of change of the centroid of the captured image. An air curtain made by the jetting high-pressure air in front of the lens was devised to prevent the vision system from being contaminated by scattered coolant, cutting chips in cutting process. To embed the vision system to a Siemens PC-NC controller 840D NC, an HMI(Human Machine Interface) program was developed under the Windows 95 operating system of MMC103. The developed HMI is placed in a sub window of the main window of 840D and this program can be activated or deactivated either by a soft key on the operating panel or M codes in the NC part program. As the tool breakage is detected, the HMI program emit a command for automatic tool change or send alarm to the NC kernel. Evaluation test in a high speed tapping center showed the developed system was successful in detection of the small-radius tool breakage.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.57-66
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper proposes hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme, The validity of the proposed controller is verified by results at different dynamic operating conditions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.5
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• pp.1095-1101
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• 2012

This paper presents a design of a BLDC servo motor control system for the auto process of assembly and supply using DSP(Digital Signal Processor) controller and IGBT driver. The assembly and supply auto processing system needs torque, speed, position control of servo motor for variable action. This paper implements those servo control with vector control and space vector PWM(Pulse Width Modulation) technique. As CPU of controller, TMS320F240 DSP was adopted because it has PWM waveform generator, A/D converter, SPI(Serial Peripheral Interface) port and many input/output port etc. This control system consists of 3-level hierarchy structure that main host PC manages three sub DSP system which transfer downward command and are monitoring the states of end servo controllers. Each sub DSP system operates eight BLDC servo controllers which control BLDC motor using DSP and IPM. Between host system and sub DSP communicate with RS-422, between main processor and controller communicate with SPI port.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.3
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• pp.433-441
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• 2022

In general, in an emergency generator system for an electric facility including an induction motor load, an emergency power generation facility larger than the facility load capacity is built due to the initial starting current of the induction motor. In order to reduce this economic burden, various methods to reduce the inrush current of induction motors are applied to suppress the additional expansion of generators due to the reduction of power generation facilities and the increase in electrical facilities. Among these methods, when a system with a built-in soft start function of an induction motor using an inverter is built, it is the best way to reduce the inrush current of the induction motor to less than the rated current. However, in this case, the installation cost of the inverter to drive the induction motor increases. This paper proposes a soft start method of an induction motor by expanding the frequency and voltage control operation area of an emergency generator. In addition, proposed a speed calculation method based on power factor information, which is essential information for stable soft start of an induction motor, and a method for generating a speed command value of the governor for starting with maximum torque.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.5
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• pp.223-229
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• 2023

This Paper propose the method that measure main system parameters for PI(proportional-integral) current control of a.c. motor adopting the vector control technique. For current control, the PI control input is could be tuning by several selective methods. Among the several methods, the method that using the main system parameters, wire resistance and inductance, are frequently used. In this study, the technique to dissect and measure these two system parameters through the results of simple feedback control. This analytic measurement method is measuring parameters step by step dissecting the results of P control using simple proportional feedback gain about the unit step or multiple step reference command. This strategy is an real time analytic measurement method that calculate current control gains of torque component and flux component both for vector control of A.C. motor without introducing the further measurement circuits and complex measuring algorithms.