• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.451-456
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• 2014

A compact model of a depletion-mode silicon-nanowire (Si-NW) pH sensor is proposed. This drain current model is obtained from the Pao-Sah integral and the continuous charge-based model, which is derived by applying the parabolic potential approximation to the Poisson's equation in the cylindrical coordinate system. The threshold-voltage shift in the drain-current model is obtained by solving the nonlinear Poisson-Boltzmann equation for the electrolyte. The simulation results obtained from the proposed drain-current model for the Si-NW field-effect transistor (SiNWFET) agree well with those of the three-dimensional (3D) device simulation, and those from the Si-NW pH sensor model also agree with the experimental data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.22 no.3
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• pp.66-73
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• 2008

This paper presents a position sensorless control system of SRM over wide speed range. Due to the doubly salient structure of the SRM, the phase inductance varies along with the rotor position. Most of the sensorless control techniques are based on the fact that the magnetic status of the SRM is a function of the angular rotor position. The rotor position estimation of the SRM is somewhat difficult because of its highly nonlinear magnetizing characteristics. In order to estimate more accurate rotor position over wide speed range, Neural Network is used for this highly nonlinear function approximation. Magnetizing data patterns of the prototype 1-hp SRM are obtained from locked rotor test, and used for the Neural Network training data set. Through measurement of the flux-linkage and phase currents, rotor position is able to estimate from current-flux-rotor position lookup table which is constructed from trained Neural Network. Experimental results for a 1-hp SRM over 16:1 speed range are presented for the verification of the proposed sensorless control algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.3 no.1
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• pp.46-52
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• 1998

This paper describes a current-shaping method for the production of constant torque of SRM under the nonlinear magnetic saturation condition. A current detection technique in the inductance increasing region and an approximation technique for modeling of nonlinear inductance profile are adopted. In the proposed system, a single switching angle control and voltage control is used to shape the current waveform for the generation of flat torque at any given load condition. Finally the validity of the proposed method was verified using a constructed 3HP 6/4 SRM.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.993-1000
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• 2001

Configuration-dependent nonlinear coefficient matrices in the dynamic equation of robot manipulator impose computa- tional burden in real-time implementation of tracking control based on the inverse dynamics controller. However, parallel manipulators such as Stewart platform have relatively small workspace compared to serial manipulators. Based on the characteristics of small motion range. nonlinear coefficient matrices can be approxiamted to constant ones. The modeling errors caused by such approximation are compensated for by H-infinity controller that treats the modeling errors disturbance. The proposed inverse dynamics controller with approximate dynamics combined with H-infinity control shows good tracking performance even for fast tracking control in which computation of full inverse dynamics is not easy to implement.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 1995.05a
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• pp.141-153
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• 1995

An incremental Total Lagrangian Formulation is implemented for the finite element analysis of laminated composite pressure vessel with consideration of the material and geometric nonlinearities. For large displacements/large rotations due to geometric nonlinearities, the incremental equations are derived using a quadratic approximation for the increment of the reference vectors in terms of the nodal rotation increments. This approach leads to a complete tangent stiffness matrix. For material nonlinearity, the analysis is performed by using the piecewise linear method, taking account of the nonlinear shear stress-strain relation. The results of numerical tests include the large deflection behavior of the selected composite shell problem. When compared with the previous analysis, tile results are in good agreement with them. As a practical example, filament wound pressure vessel is analyzed with consideration of the geometrically and materially nonlinearity. The numerical results agree fairly well with the existing experimental results.

• Structural Engineering and Mechanics
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• v.56 no.3
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• pp.461-472
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• 2015

In this paper, the nonlinear static response of curled cantilever beam actuators subjected to the one-sided electrostatic field is focused on. By assuming the deflection function of electrostatically actuated beam, analytical approximate solutions are established via using Galerkin method to solve the equilibrium equation. The Pull-In voltages which determine the stability of the curled beam actuators are also obtained. These approximate solutions show excellent agreements with numerical solutions obtained by the shooting method and the experimental data for a wide range of beam length. Expressions of these analytical approximate solutions are brief and could easily be used to derive the effects of various physical parameters on MEMS structures.

• Journal of Biomedical Engineering Research
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• v.15 no.1
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• pp.57-62
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• 1994

The demand of image compression is increasing now for the integration of medical images into the hospital information system. Even though the quantitative distortion can be measured from the difference between original and reconstructed images, it doesn't include the nonlinear characteristics of human visual system. In this study, we have evaluated the nonlinear characteristics of human visual system and applied them to the compression of medical images. The distortion measures which reflect the characteristics of human visual system has been considered. This image compression procedure consists of coding scheme using JND (Just Noticeable Difference) curve, polynomial approximation and BTC (Block Truncation Coding). Results show that this method can be applied to CT images, scanned film images and other kinds of medical images with the compression ratio of 5-10:1 without any noticeable distortion.

• Structural Engineering and Mechanics
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• v.29 no.1
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• pp.37-53
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• 2008

Plane steel portal frames, with pitched roof, exposed to fire, are examined. First, a determinate frame is analysed by hand. For flexible columns and shallow roof, snap-through occurs before plastic hinges mechanism is formed. An indeterminate frame with shorter columns and taller roof is also analysed by hand. Then, the same frame is simulated by a truss and a nonlinear static analysis is performed by use of a short computer program. The results of computer analysis by use of truss model are compared with those of analysis by hand and a satisfactory approximation between them is observed.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.