• International Journal of Aeronautical and Space Sciences
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• v.4 no.1
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• pp.99-109
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• 2003

Attitude control law synthesis for the three-axis attitude maneuver of a flexible spacecraft model is presented in this study. The basic idea is motivated by previous works for the extension into a more general case. The new case includes gravitational gradient torque which has significant effect on a wide range of low earth orbit missions. As the first step, the fully nonlinear dynamic equations of motion are derived including gravitational gradient. The control law design based upon the Lyapunov approach is attempted. The Lyapunov function consists of a weighted combination of system kinetic and potential energy. Then, a set of stabilizing control law is derived from the basic Lyapunov stability theory. The new control law is therefore in a general form partially validating the previous work in some sense.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.5
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• pp.249-256
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• 1999

This paper describes static characteristics analysis of linear pulse motor(LPM) with two permanent magnets. Linear pulse motors are finding a wide range of application for the Factory-Automation or the Office-Automation. Typically, LPM provides for a reliable and precise control of position, velocity, or acceleration without using a closed-loop system. Some of the advantages of LPMs are ease of control, step multiplication, static and dynamic positioning, and locking force. The flux density and thrust of LPM is computed by the FEM and magnetic equivalent circuits which considered the magnetic nonlinear phenomena. The result of characteristics analysis are shown as the flux, the air gap reluctance and the thrust. The velocity and position characteristics as a function of unit step input is measured. To estimate the unit step response charecteristic of LPM, the simulation results by Matlab and the experimental results is compared.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.627-629
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• 1997

In this paper, fuzzy logic system equipped with the back-propagation training algorithm as identifiers for nonlinear dynamic systems is described. To improve its performance, Jacob's delta-bar -delta rule is adapted in adjusting stepsize ${\alpha}$, and only y and ${\alpha}$ updating algorithm is suggested. In identifying and predicting the chaotic time series, suggested method is better than Li-Xin Wang's method,[1]

• Smart Structures and Systems
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• v.18 no.1
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• pp.183-196
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• 2016

In this paper a nonlinear, bistable, single degree of freedom system is considered. It consists of a Duffing oscillator externally excited by a non-resonant, harmonic force. A customized perturbation scheme is proposed to achieve an approximate expression for periodic solutions. It is based on the evaluation of the quasi-steady (slow) solution, and then on a variable change followed by two perturbation steps which aim to capture the fast, decaying contribution of the response. The reconstructed solution, given by the sum of the slow and fast contributions, is in a good agreement with the one obtained by numerical integration.

• Smart Structures and Systems
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• v.5 no.4
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• pp.469-482
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• 2009

The emerging sensor-based structural health monitoring (SHM) technology has a potential for cost-effective maintenance of aging civil infrastructure systems. The author proposes to integrate continuous and global monitoring using on-structure sensors with targeted local non-destructive evaluation (NDE). Significant technical challenges arise, however, from the lack of cost-effective sensors for monitoring spatially large structures, as well as reliable methods for interpreting sensor data into structural health conditions. This paper reviews recent efforts and advances made in addressing these challenges, with example sensor hardware and health monitoring software developed in the author's research center. The hardware includes a novel fiber optic accelerometer, a vision-based displacement sensor, a distributed strain sensor, and a microwave imaging NDE device. The health monitoring software includes a number of system identification methods such as the neural networks, extended Kalman filter, and nonlinear damping identificaiton based on structural dynamic response measurement. These methods have been experimentally validated through seismic shaking table tests of a realistic bridge model and tested in a number of instrumented bridges and buildings.

• Journal of the Society of Naval Architects of Korea
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• v.32 no.2
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• pp.56-67
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• 1995

In this paper, a ship-cable-vehicle system's static configuration is shown obtained by solving cable nonlinear statics. Eigenfrequencies of the cable were calculated by the frequency domain analysis application of the linearized cable dynamic equations. Also extreme tensions in a slack-and-snapping long vertical cable were calculated by the clip-ping-off model.

• International Journal of Control, Automation, and Systems
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• v.3 no.1
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• pp.43-55
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• 2005

In this paper, a predictive control method using self-recurrent wavelet neural network (SRWNN) is proposed for chaotic systems. Since the SRWNN has a self-recurrent mother wavelet layer, it can well attract the complex nonlinear system though the SRWNN has less mother wavelet nodes than the wavelet neural network (WNN). Thus, the SRWNN is used as a model predictor for predicting the dynamic property of chaotic systems. The gradient descent method with the adaptive learning rates is applied to train the parameters of the SRWNN based predictor and controller. The adaptive learning rates are derived from the discrete Lyapunov stability theorem, which are used to guarantee the convergence of the predictive controller. Finally, the chaotic systems are provided to demonstrate the effectiveness of the proposed control strategy.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2763-2765
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• 2000

The interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition. operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller (FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Expeiments are carried out to check the performance of the FLC.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.73-75
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• 1998

In this paper, a transient analysis method of Switched Reluctance Motors(SRM) is presented. The Finite Element Method(FEM) is used to model the nonlinear magnetic field and is coupled to the power circuits and mechanical system. The time derivative term in the differential equation is formulated by the time difference method. The proposed method is applied to a 4 phase 16/12 SRM to study starting characteristics and an fault due to the failure of a transistor in the converter.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2333-2335
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• 2000

The main motivation of this research is to develop an intelligent control strategy for Activated Sludge Process(ASP). ASP is a complex and nonlinear dynamic system because of the characteristic of a wastewater, the change of an influent flow rate, weather conditions, and etc. The mathematical model of ASP also includes uncertainties which are ignored or not considered by process engineer or controller designer. The ASP is generally controlled by a PID controller that consists of fixed proportional, integral, and derivative gain values. The PID gains can be adjusted by the expert in the ASP. The ASP model based on Matlab$^{(R)}$5.3/Simulink$^{(R)}$3.0 is developed in this paper. Various control methods are applied to the ASP model and the control results are disscussed. Three control methods are designed and tested: conventional PID controller, fuzzy logic control approach to modify setpoints, and fuzzy-PID control method.