• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.691-695
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• 1998

Most of systems has nonlinearity . And also accurate modelings of these uncertain nonlinear systems are very difficult. In this paper, a fuzzy modeling technique for the stabilization control of an IP(inverted pendulum) system with nonlinearity was proposed. The fuzzy modeling was acquired on the basis of ANFIS(Adaptive Neuro Fuzzy Infernce System) which could learn using a series of input-output data pairs. Simulation results showed its superiority to the PID controller. We believe that its applicability can be extended to the other nonlinear systems.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2305-2307
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• 2000

In this paper we propose a Neuro-Fuzzy modeling method using mGA for complex nonlinear system. mGA has more effective and adaptive structure than sGA with respect to using the changeable-length string. This paper suggest a new coding method for applying the model's input and output data to the number of optimul rules of fuzzy models and the structure and parameter identifications of membership function simultaneously. The proposed method realize optimal fuzzy inference system using the learning ability of Neural network. For fine-tune of the identified parameter by mGA, back-propagation algorithm used for optimulize the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through compare with ANFIS.

• Journal of electromagnetic engineering and science
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• v.8 no.1
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• pp.17-22
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• 2008

It is presented that sampling rates for behavioral modeling of quasi-memory less nonlinear devices can be far less than the Nyquist rate of the input signal. Although it has been believed that the sampling rate of nonlinear device modeling should be at least the Nyquist rate of the output signal, this paper suggests that far less than the Nyquist rate of the input signal can be applied to the modeling of quasi-memoryless nonlinear devices, such as frequency multipliers. To verify, a QPSK signal at 820 MHz were applied to a frequency tripler, whereby the device can be utilized as an up-converting mixer into 2.46 GHz with the aid of digital predistortion. AM-AM, AM-PM and PM-PM can be successfully measured regardless of sampling rates.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.1952-1954
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• 2001

In this paper, we propose the neuro-fuzzy modeling method using VmGA (Virus messy Genetic Algorithm) for the complex nonlinear system. VmGA has more effective and adaptive structure than sGA. in this paper, we suggest a new coding method for applying the model's input and output data to the optimal number of rules in fuzzy models and the structure and parameter identification of membership functions simultaneously. The proposed method realizes the optimal fuzzy inference system using the learning ability of neural network. For fine-tune of parameters identified by VmGA, back- propagation algorithm is used for optimizing the parameter of fuzzy set. The proposed fuzzy modeling method is applied to a nonlinear system to prove the superiority of the proposed approach through comparing with ANFIS.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.96-101
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• 2008

The field of load modeling has attracted the attention since it plays an important role for improving the accuracy of stability analysis and power flow estimation. Also, load modeling is an essential factor in the simulation and evaluation of power system performance. However, conventional load modeling techniques have some limitations with respect to accuracy for nonlinear and composite loads. Thus, precision load modeling technique and reasonable application method is needed for more accurate power system analysis. In this paper, we develop an intelligent load modeling method based. on neural network and application techniques for power system. The proposed method makes it possible to effectively estimate the load model for nonlinear models as well as linear models. Reasonable application method is also proposed for stability analysis. To demonstrate the validity of the proposed method, various experiments are performed and their results are presented.

• Journal of The Korean Digital Architecture Interior Association
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• v.13 no.4
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• pp.5-12
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• 2013

Conceptual and technical design designated as digital architecture has been discussed with disorderly meaning as a conception only. Thus, this study aims at verification of development possibility for the digital architecture by analyzing how works of Frank Gehry have effect on nonlinearity of the digital architecture. Nonlinear characteristics appeared on works of Frank Gehry analyzed on the basis of expression techniques and modeling principle are as follows: 1) Initial works show a trend to gradually change and develop from horizontal and vertical linear structure to nonlinear pattern. 2) From a nonlinear modeling principle, initial works appear the primary deformation elements only, while afterwards, they are gradually developing to a pattern to mix the primary and secondary deformation elements as introduction of digital architecture. 3) Through specific cases, Frank Gehry has conducted attempts with various method for nonlinear pattern expression. 4) From the initial works to the latest works, continuity becomes higher and changed to nonlinear pattern. This study is significant from a viewpoint that it has verified development possibility of digital architecture by analyzing nonlinear trend of digital architecture for Frank Gehry and it is required to conduct multilateral researches related to the digital architecture.

• Structural Engineering and Mechanics
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• v.37 no.1
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• pp.111-129
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• 2011

This paper presents a nonlinear analysis of reinforced concrete column with lap splice confined by FRP wrapping in the critical hinging zone. The steel stress-slip model derived from the tri-uniform bond stress model presented in the companion paper is included in the nonlinear frame analysis to simulate the response of reinforced concrete columns subjected to cyclic displacement reversals. The nonlinear modeling is based on a fiber discretization of an RC column section. Each fiber is modeled as either nonlinear concrete or steel spring, whose load-deformation characteristics are calculated from the section of fiber and material properties. The steel spring that models the reinforcing bars consists of three sub-springs, i.e., steel bar sub-spring, lap splice spring, and anchorage bond-slip spring connected in series from top to bottom. By combining the steel stress versus slip of the lap splice, the stress-deformation of steel bar and the steel stress-slip of bars anchored into the footing, the nonlinear steel spring model is derived. The analytical responses are found to be close to experimental ones. The analysis without lap splice springs included may result in an erroneous overestimation in the strength and ductility of columns.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.1
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• pp.42-54
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• 2009

Contrast to the 6-DOF nonlinear dynamic modeling of nonlinear tracking problem, 3-DOF point-mass modeling of flight mechanics is efficient and adequate for applying the trajectory optimization problem. There exist limitations to apply an optimal trajectory from point-mass modeling as a reference trajectory directly to conduct the nonlinear tracking control, In this paper, new matching trajectory optimization scheme is proposed to compensate those differences of mismatching. To verify performance of proposed method, full ascent three-dimensional flight trajectories are obtained by reflecting the real constraints of flight conditions and airship performance with and without jet stream condition. Then, they are compared with the optimal trajectories obtained from conventional method.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.10
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• pp.127-136
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• 2004

This paper is the first of two companion papers concerning the analysis and design of a pneumatic vibration isolation system. The design optimization of the pneumatic vibration isolation system is required for the reduction of cost, endeavor and time, and it needs modeling and calculation algorithm. The nonlinear models are devised from the fluid mechanical expression for components of the system and the calculation algorithm is derived from the mathematical relationship between the models. It is shown that the orifice makes the nonlinear property of the transmissibility curve that the resonant frequency changes by the amplitude of excited vibration. Linearization of the nonlinear models is tried to reduce elapsed time and truncation error accumulation and to enable the transmissibility calculation of the system with multi damping chambers. The equivalent mechanical models generated by linearization clarify the function of each component of the system and lead to the linearized transfer function that can give forth to the transmissibility exactly close to that of nonlinear models. The modified successive under-relaxation method is developed to calculate the linearized transfer function.