• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.12
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• pp.1864-1871
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• 2012

This paper proposes the hybrid proportional integral(HBPI) controller for maximum power point tracking(MPPT) control of photovoltaic system. The output characteristics of the solar cell are a nonlinear and affected by a temperature, the solar radiation and influence of a shadow. The MPPT control is a very important technique in order to increase an output and efficiency of the photovoltaic system. The conventional constant voltage(CV), perturbation and observation(PO) and incremental conductance(IC) are the method which finding maximum power point(MPP) by the continued self-excitation vibration, and uses the fixed step size. If the fixed step size is a large, the tracking speed of maximum power point is faster, but the tracking accuracy in the steady state is decreased. On the contrary, when the fixed step size is a small, the tracking accuracy is increased and the tracking speed is slower. Therefore, in order to solve these problems, this paper proposes HBPI controller that is adjusted gain of conventional PI control using fuzzy control, and the maximum power point tracks using this controller. The validity of the controller proposed in this paper proves through the results of the comparisons.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.408-411
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• 2009

In this paper, conventional PI, fuzzy neural network(FNN) and adaptive teaming mechanism(ALM)-FNN for rotor field oriented controlled(RFOC) induction motor are studied comparatively. The widely used control theory based design of PI family controllers fails to perform satisfactorily under parameter variation nonlinear or load disturbance. In high performance applications, it is useful to automatically extract the complex relation that represent the drive behaviour. The use of learning through example algorithms can be a powerful tool for automatic modelling variable speed drives. They can automatically extract a functional relationship representative of the drive behavior. These methods present some advantages over the classical ones since they do not rely on the precise knowledge of mathematical models and parameters. Comparative study of PI, FNN and ALM-FNN are carried out from various aspects which is dynamic performance, steady-state accuracy, parameter robustness and complementation etc. To have a clear view of the three techniques, a RFOC system based on a three level neutral point clamped inverter-fed induction motor drive is established in this paper. Each of the three control technique: PI, FNN and ALM-FNN, are used in the outer loops for rotor speed. The merit and drawbacks of each method are summarized in the conclusion part, which may a guideline for industry application.

• 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.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.828-833
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• 2009

WWW which is an applicable massive set of document on the Web is a thesaurus of various information for users. However, Search engines spend a lot of time to retrieve necessary information and to filter out unnecessary information for user. In this paper, we propose the EFAM(the Extended Fuzzy AHP Method) model to manage the Web resource efficiently, and to make a decision in the problem of specific domain definitely. The EFAM model is concerned with the emotion analysis based on the domain corpus information, and it composed with systematic common concept grids by the knowledge of multiple experts. Therefore, The proposed the EFAM model can extract the documents by considering on the emotion criteria in the semantic context that is extracted concept from the corpus of specific domain and confirms that our model provides more efficient decision-making through an experiment than the conventional methods such as AHP and Fuzzy AHP which describe as a hierarchical structure elements about decision-making based on the alternatives, evaluation criteria, subjective attribute weight and fuzzy relation between concept and object.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.307-311
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• 2003

2-mass system is generally used as controller of the variable-speed to transfer electromotion power to mechanical load such as industrial robot, driving parts of electric vehicle, rolling machine system of steel plant and driving parts of elevator. In this case, PI controller is often used as a velocity controller because of simplicity of system. But PI control algorithm is not enough for obtaining the control characteristics required for this system. To solve this problem, 2-mass system based on the PID controller derives the optimum PID parameters by pole assignment and estimation of the ITAE performance index. In this case, the system have tenacious properties about disturbance, but it causes extreme overshoot and vibration because of rapidly output of controller in early transient response about desired value. And if speed control system is applied by 2-DOF parameter ${\alpha}$, a temporary value, we must induce most suitable parameter by complicate pole assignment and estimation of the ITAE performance index whenever ${\alpha}$ changes. In this paper, to solve this problem we suggest control algorithm to followed exactly value of ${\alpha}$ as 2-DOF parameter by using fuzzy algorithm . So, intelligence algorithm modeled by human knowledge, experience, teachability and judgment follow exact ${\alpha}$ value and it can compose the efficient 2-DOF PID controller to improve following performance, overshoot decrease.

• Journal of Power Electronics
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• v.14 no.3
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• pp.444-457
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• 2014

This paper presents the design and realization of a digital PV simulator with a Push-Pull Forward (PPF) circuit based on the principle of modular hardware and configurable software. A PPF circuit is chosen as the main circuit to restrain the magnetic biasing of the core for a DC-DC converter and to reduce the spike of the turn-off voltage across every switch. Control and I/O interface based on a personal computer (PC) and multifunction data acquisition card, can conveniently achieve the data acquisition and configuration of the control algorithm and interface due to the abundant software resources of computers. In addition, the control program developed in Matlab/Simulink can conveniently construct and adjust both the models and parameters. It can also run in real-time under the external mode of Simulink by loading the modules of the Real-Time Windows Target. The mathematic models of the Push-Pull Forward circuit and the digital PV simulator are established in this paper by the state-space averaging method. The pole-zero cancellation technique is employed and then its controller parameters are systematically designed based on the performance analysis of the root loci of the closed current loop with $k_i$ and $R_L$ as variables. A fuzzy PI controller based on the Takagi-Sugeno fuzzy model is applied to regulate the controller parameters self-adaptively according to the change of $R_L$ and the operating point of the PV simulator to match the controller parameters with $R_L$. The stationary and dynamic performances of the PV simulator are tested by experiments, and the experimental results show that the PV simulator has the merits of a wide effective working range, high steady-state accuracy and good dynamic performances.

• Advances in materials Research
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• v.1 no.2
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• pp.129-146
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• 2012

Polycrystalline diamond is an ideal material for parts with micro-holes and has been widely used as dies and cutting tools in automotive, aerospace and woodworking industries due to its superior wear and corrosion resistance. In this research paper, the modeling and simultaneous optimization of multiple performance characteristics such as material removal rate and surface roughness of polycrystalline diamond (PCD) with ultrasonic machining process has been presented. The fuzzy logic and taguchi's quality loss function has been used. In recent years, fuzzy logic has been used in manufacturing engineering for modeling and monitoring. Also the effect of controllable machining parameters like type of abrasive slurry, their size and concentration, nature of tool material and the power rating of the machine has been determined by applying the single objective and multi-objective optimization techniques. The analysis of results has been done using the MATLAB 7.5 software and results obtained are validated by conducting the confirmation experiments. The results show the considerable improvement in S/N ratio as compared to initial cutting conditions. The surface roughness of machined surface has been measured by using the Perthometer (M4Pi, Mahr Germany).

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1006-1011
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• 2004

Recently, technical trend in machine tools is focused on enhancing of speed, accuracy and reliability. Such high speed usually results in thermal displacement and structural deformation. To minimize such thermal effect, most precision machine tools adopt high precision cooling system. This study proposes a temperature control for an oil cooler system using PI control with fuzzy logic. In a cooler system, the refrigerant flow rate is controlled by rotational speed of the compressor, where the outlet oil temperature is selected as the control variable. The fuzzy control rules iteratively correct PID parameters to minimize the error, difference between the outlet temperature and the reference one. Here, the ambient temperature is used as the reference one. To show the effectiveness of the proposed method, a series of experiments are conducted for an oil cooler system of machine tools, and the results are compared with the ones of a conventional PID control. The experimental results show that the proposed method has advantages of smaller overshoot and smaller steady state error.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.2
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• pp.109-114
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• 2002

Various inverted pendulum systems have been frequently used as a model for the performance test of the proposed control system. We first identify a rotary-type inverted pendulum system by the Euler-Lagrange method and then design a FLC (Fuzzy Logic Controller) fur the plant. FLC`s are one of useful control schemes fur plants having difficulties in deriving mathematical models or having performance limitations with conventional linear control schemes. Many FLC`s imitate the concept of conventional PD (Proportional-Derivative) or PI (Proportional-Integral) controller. That is, the error e and the change-of-error are used as antecedent variables and the control input u the change of control input Au is used as its consequent variable for FLC`s. In this paper we design a simple-structured FLC for the rotary inverted pendulum system. We also perform some computer simulations to examine the tracking performance of the closed-loop system.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.243-244
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• 2008

In this paper proposed the solar tracking system to use a fuzzy based on PC in order to increase an output of the PV array. The solar tracking system operated two DC motors driving by signal of photo sensor. The control of dual axes is not an easy task due to nonlinear dynamics and unavailability of the parameters. The fuzzy control made a nonlinear dynamics to well perform and had a robust and highly efficient characteristic about a parameter variable as well as a nonlinear characteristic. In this paper designed a fuzzy controller for improving output of PV array and evaluated comparison with efficient of conventional PI controller. The data which were obtained by experiment were able to show a validity of the proposed controller.