• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.3
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• pp.281-289
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• 2016

In this paper, a new dynamic model for modal analysis of a rotating cantilever beam with a tip-mass is developed. The nonlinear strain such as von Karman type and the corresponding linearized stress are used to consider the geometric nonlinearity, and Euler-Bernoulli beam theory is applied in the present model. The nonlinear equations of motion and the associated boundary conditions which include the inertia of the tip-mass are derived through Hamilton's principle. In order to investigate modal characteristics of the present model, the linearized equations of motion in the neighborhood of the equilibrium position are obtained by using perturbation technique to the nonlinear equations. Since the effect of the tip-mass is considered to the boundary condition of the flexible beam, weak forms are used to discretize the linearized equations. Compared with equations related to stiffening effect due to centrifugal force of the present and the previous model, the present model predicts the dynamic characteristic more precisely than the another model. As a result, the difference of natural frequencies loci between two models become larger as the rotating speed increases. In addition, we observed that the mode veering phenomenon occurs at the certain rotating speed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.184-191
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• 2009

In a technological driven environment, a depreciation estimate which is based on traditional life analysis results in a decelerated rate of capital recovery. This time pattern of technological growths models needs to be incorporated into life analysis framework especially in those industries experiencing fast technological changes. The approximation technique for calculating the variance can be applied to the six growth models that were selected by the degree of skewness and the transformation of the functions. For the Pearl growth model, the Gompertz growth model, and the Weibull growth model, the errors have zero mean and a constant variance over time. However, transformed models like the linearized Fisher-Pry model, the linearized Gompertz growth model, and the linearized Weibull growth model have increasing variance from zero to that point at which inflection occurs. It can be recommended that if the variance of error over time is increasing, then a transformation of observed data is appropriate.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.618-623
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• 1992

In this paper robotic manipulators in which the joints exhibit a certain amount of elasticity are considered. Based on a feedback linearized model, sliding mode control system is designed. In the control system design, weak joint stiffness assumption does not needed. Simulation results are presented to verify the validity of the control scheme. A robustness analysis for a feedback linearized model is also given with respect to uncertainties on the robot parameters.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.636-643
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• 1998

This paper is presents multivariable control scheme for industrial robot manipulators. The control scheme consists of two loops. The modeling error between linearized robot model and actual robot model is compensated in error compensation loop. The PID control loop is designed for pole assignment to stability of robot system and utilized for trajectory tracking. Alternatively computer simulation results are given for illustration purpose of suggested controller.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.11a
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• pp.185-188
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• 1997

In this paper, we execute identification, linearization, and control of a nonlinear system using recurrent neural networks. In general nonlinear control system become complex because of nonlinearity and uncertainty. And though we compose nonlinear control system based on the model, it is difficult to get good control ability. So we identify the nonlinear control system using the recurrent neural networks and execute feedback linearization of identified model, In this process we choose the optional linear system, and the system which will have to be feedback linearized if trained to follow the linearity between input and output of the system we choose. We the feedback linearized system by applying standard linear control strategy and simulation. And we evaluate the effectiveness by comparing the result which is linearized theoretically.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.1
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• pp.62-68
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• 1996

Linear controllers, such as LQG/LTR controller, have been investigated to control flexible link manipulators. The performance and complexity of these depend largely on the linearized model upon which the controller is designed. In this study, singular perturbation model is tested in designing a LQG/LTR controller for a flexible link manipulator. The order of the resulting controller is much lower than the one based on a full model. Through numerical study, it is shown that the performance of the proposed controller reaches reasonably to the one based on the full model.

• Journal of KSNVE
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• v.3 no.3
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• pp.231-243
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• 1993

The dynamic characteristics of two types of mathematical models for a rigid body suspension system are analyzed and compared in this paper. One is a linearized model which is commonly used in the engine mount system analysis, the other is a nonlinear model which usually applied to the pendulum type system. The typical 3 d.o.f's mathematical model, for convenience, is chosen as a simulation model, because it has fundamental dynamic characteristics of suspension system. Time responses and unbalance responses of the rigid body, transmitted forces and torques are simulated by using the mathematical model. From the results of computer simulation, it is approved that he nonlinear model is valid and the linearized model gives erroneous results in the case of the pendulum type suspension system. In addition, in this study the effects of design change on the dynamic characteristics of the suspension system are investigated. Mount locations, mount angles, lengths, stiffness and damping coefficients of suspension bars are chosen as design parameters.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.895-905
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• 1999

This paper identifies a linear time-invariant mathematical model of each stand of a five-stand tandem cold mill to design a robust $H_\infty$ thickness controller by applying input and output data sets to N4SID (Numerical algorithms for Subspace State Space System Identification) method. The input-output data sets describe interstand interference in the process of tandem cold rolling and are obtained from a nonlinear simulator of the tandem cold mill. In result, it is shown that the identified model well approximates the nonlinear model than a Taylor linearized model. Furthermore, uncertainties including roll eccentricity and incoming strip variation are quantitatively analyzed from the plot of maximum singular values.

• Journal of the Korean Mathematical Society
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• v.55 no.3
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• pp.719-734
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• 2018

An image restoration problem with Poisson noise arises in many applications of medical imaging, astronomy, and microscopy. To overcome ill-posedness, Total Variation (TV) model is commonly used owing to edge preserving property. Since staircase artifacts are observed in restored smooth regions, higher-order TV regularization is introduced. However, sharpness of edges in the image is also attenuated. To compromise benefits of TV and higher-order TV, the weighted sum of the non-convex TV and non-convex higher order TV is used as a regularizer in the proposed variational model. The proposed model is non-convex and non-smooth, and so it is very challenging to solve the model. We propose an iterative reweighted algorithm with the proximal linearized alternating direction method of multipliers to solve the proposed model and study convergence properties of the algorithm.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.221-227
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• 2000

This paper combines the constrained model predictive control with the feedback linearization to solve a nonlinear system control problem with input constraints. The combined approach consists of two steps: Firstly, the nonlinear model is linearized by the feedback linearization. Secondly, based on the linearized model, the constrained model predictive controller is designed taking input constraints into consideration. The proposed controller is applied to two link robot system, and tracking performances of the controller are investigated via some simulations, where the comparisons are done for the cases of unconstrained, constrained input in feedback linearization.