• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.1
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• pp.111-118
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• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of computational fluids engineering
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• v.19 no.4
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• pp.20-28
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• 2014

An efficient solution algorithm for simulating free surface problem is presented. Navier-Stokes equations for variable density incompressible flow are employed as the governing equation on Cartesian meshes. In order to describe the free surface motion efficiently, VOF(Volume Of Fluid) method utilizing THINC(Tangent of Hyperbola for Interface Capturing) scheme is employed. The most time-consuming part of the current free surface flow simulations is the solution step of the linear system, derived by the pressure Poisson equation. To solve a pressure Poisson equation efficiently, the PCG(Preconditioned Conjugate Gradient) method is utilized. This study showed that the proper application of the preconditioner is the key for the efficient solution of the free surface flow when its pressure Poisson equation is solved by the CG method. To demonstrate the efficiency of the current approach, we compared the convergence histories of different algorithms for solving the pressure Poisson equation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.4
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• pp.267-275
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• 2004

This research is concerned with the development of a real-time adaptive PPF controller for the active vibration suppression of smart structure. In general, the tuning of the PPF controller is carried out off-line. In this research, the real-time learning algorithm is developed to find the optimal filter frequency of the PPF controller in real time and the efficacy of the algorithm is proved by implementing it in real time. To this end, the adaptive algorithm is developed by applying the gradient descent method to the predefined performance index, which is similar to the method used popularly in the optimization and neural network controller design. The experiment was carried out to verify the validity of the adaptive PPF controller developed in this research. The experimental results showed that adaptive PPF controller is effective for active vibration control of the structure which is excited by either impact or harmonic disturbance. The filter frequency of the PPF controller is tuned in a very short period of time thus proving the efficiency of the adaptive PPF controller.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.1
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• pp.81-87
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• 1997

Coagulation is very important process in water works. The subsequent processes are directly affected by this process. Many factors such as turbidity, alkalinity, pH, hardness, total organic carbon(TOC), velocity gradient and flocculation time effect on coagulation process. Among these factors, specially TOC is being concerned target substance to be removed due to trihalomenthanes(THMs) precursor and alkalinity is being one of the major parameter for removing TOC. We have researched the consumption of coagulant with TOC alkalinity concentration of water and removal efficiency of residual TOC and turbidity with alkalinity. Furthermore we have investigated particle size distributions with velocity gradient and alkalinity. The consumption of coagulant was proportionally increased to TOC and alkalinity concentration and the removal of TOC in Nakdong river water was very difficult more than 150 mg/l in alkalinity but large morecular weight organic such as humic acid could be removed easily. Coagulation of low alkalinity water was more rapidly occured than of high alkalinity water by analyzing the particle size distributions. High alkalinity water needed higher mixing energy for a good coagulation within limited flocculation time.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.1
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• pp.24-30
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• 2003

In this paper, we propose a novel predictive control method, which uses a wavelet neural network as a predictor, for the control of chaotic systems. In our method, we use the gradient descent method for training the parameter of a wavelet neural network. The control signals are directly obtained by minimizing the difference between a reference signal and the output of a wavelet neural network. To verify the efficiency of our method, we apply it to the Doffing and the Henon system, which are a representative continuous and discrete time chaotic system respectively, and compare with the results of generalized predictive control using multi-layer perceptron.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.5
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• pp.845-851
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• 2008

A simple RMRAC (Robust Model Reference Adaptive Control) scheme for the PMSM (Permanent Magnent Synchronous Motor) is proposed in the synchronous frame. A current control of PMSM is the most inner loop of electro-mechanical driving systems and it requires a fast and simple control law to play a foundation role in the control hierarchy. In the proposed synchronous current model, the input signal is composed of a calculated voltage by proposed adaptive laws and real system disturbance. The gains of feed-forward and feedback controllers are estimated by the proposed modified Gradient method respectively, where the system disturbances are assumed as filtered current tracking errors. After the estimation of the system disturbances from the tracking errors, the corresponding voltage is fed forward to control input voltage to compensate for the disturbances. The proposed method is robust against high frequency disturbance and has a fast dynamic response. It also shows a good real-time performance due to it's simplicity of control structure. Through the simulations and real experiments, efficiency of the proposed method is verified.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.423-431
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• 2000

This paper presents a systematic approach to the input-output data-based fuzzy modeling for the complex and uncertain nonlinear systems, in which the conventional mathematical models may fail to give the satisfying results. To do this, we propose a new method that can yield a successful fuzzy model using a mGA hybrid schemes with a fine-tuning method. We also propose a new coding method fo chromosome for applying the mGA to the structure and parameter identifications of fuzzy model simultaneously. During mGA search, multi-purpose fitness function with a penalty process is proposed and adapted to guarantee the accurate and valid fuzzy modes. This coding scheme can effectively represent the zero-order Takagi-Sugeno fuzzy model. The proposed mGA hybrid schemes can coarsely optimize the structure and the parameters of the fuzzy inference system, and then fine tune the identified fuzzy model by using the gradient descent method. In order to demonstrate the superiority and efficiency of the proposed scheme, we finally show its applications to two nonlinear systems.

• Journal of Power System Engineering
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• v.9 no.4
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• pp.220-224
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• 2005

The thermal elasto-plastic analysis for the prediction of welding distortion of a 3 dimensional large-scaled ship structure is a very time-consuming work since the analysis is a nonlinear problem, and a lot of finite elements are needed to simulate the large ship hull block. Generally, 3-D finite elements have been used in the 3-D welding distortion problem to assess precisely the temperature gradient through the thickness direction of the welding plate. As a result of the adoption of 3-D element, degrees of freedom are rapidly increased in the problem to be solved. In this study, to improve the time efficiency of welding thermal elasto-plastic analysis, a layered shell element was proposed to simulate 3-D temperature gradient, and the results were compared with the experiment. The experiments were carried out for the type of bead-on-plate welding, and we found the measured data have a good agreement with the FEA results.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.15 no.5 s.98
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• pp.595-603
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• 2005

In this work, the multiple dynamic absorber( MDA ) is introduced to reduce several vibration modes of shadow mask simultaneously and its design method is developed from the theory of the simple dynamic absorber. When designing the dynamic absorber, there are three significant design parameters such as mass, damping ratio and tuning frequency. Therefore the sensitivity analysis for those parameters has been executed in order to find out the design criteria of multiple dynamic absorber using the finite element model of shadow mask. The multiple dynamic absorber(MDA) designed by the proposed method is tested theoretically and experimentally to estimate the efficiency of vibration reduction. From the results, it is verified that the method is feasible to apply the system having the multiple nitration modes and more efficient than the thin wire-type damper used commercially to reduce the vibration of shadow mask.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.06a
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• pp.295-295
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• 2008

This study introduced waste water treatment method applied superconductor HGMS(High Gradient Magnetic Separation). HGMS method treat high efficient method for various waste water. we have surveyed superconducting magnetic separation technology and reviewed the status of related industries using applied superconductivity. We fabricated the prototypes of magnetic matrix filter consisting of stainless steel mesh, which is a core component in the magnetic separation system. In our basic preliminary experiment using HGMS, it was made clear that the fine para-magnetic particles in the rolling colling wasted water obtained from rolling process of POSCO can be separated with high efficiency.