• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.151-158
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• 2002

In the present design concept, the nonlinear behaviour of bridges is at lowed under large earthquake. The nonlinearity is, however, localized like pier, bearing, etc. Especially, pier columns are most important members for seismic performance. It is, however, difficult to solve the problem how the nonlinearity of columns should be modelled. In this study, the fiber element is used for modelling pier column. The element is a kind of structural elements like frame element, and it can model the distributed plasticity of plastic hinge. A 3 span continous bridge is taken for seismic analysis. First, the nonlinear static analysis the column at fixed support are performed so that the characteristics of column is analyzed. Second, Linear and nonlinear dynamic analysises using simplified model for longitudinal direction are carried out and the results are analyzed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1919-1925
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• 2001

Overhead cranes consist of trolley, girder, rope, objects, trolley motor, girder motor, and hoist motor. If objects are regarded as mass point, and the acceleration of hoisting motion for objects is neglected, analytical model of overhead cranes becomes a nonlinear model because the length of a rope changes. Equations of motion this model is derived of simultaneous differential equations fur motors and object. Positions of the model are controlled by optimal inputs which obtain from a nonlinear optimal control method. From the results of computer simulation, even if initial states of objects suing, it is founded that position of overhead cranes is controlled, and that swing of objects is suppressed.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.265-273
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• 2016

A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The three models are validated using Matlab with nonlinear input-output data that was not used during training.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.5
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• pp.966-972
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• 2007

This paper presents position control of nonlinear three-dimensional crane systems using neural network approach. Such crane system generally includes very complicated characteristic dynamics and mechanical framework such that its mathematical model is expressed by strong nonlinearity. This leads difficulty in control design for the systems. We linearize the nonlinear system model to construct PID control applying well-known linear control theory and then neural network is utilized to compensate system perturbation due to linearization. Thus, control input of the crane system is composed of nominal PID and neural output signals respectively. Our method illustrates simple design procedure, but system perturbation and modelling error are overcome through a neural compensator. As well. adaptive neural control is constructed from online learning. Computer simulation demonstrates our control approach is superior to the classic control systems.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.326-328
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• 1993

Modelling theory, based on differential equations, is not an adequate tool for solving the problems of complex system. Identification of complex system using GMDH(group method of data handling) is more appropriate for this problems. In this paper, GMDH algorithm is used to identify the nonlinear plant and to design model following nonlinear control system. Simulation for the DC motor show the good performance of model following nonlinear control system.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.41-49
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• 1997

In this paper, we describe the algorithm which controls an unknown nonlinear system with disturbance a using multilayer neural network. The multilayer neural network can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate an unknown nonlinear system by using of multilayer neural netowrk. WE include a disturbance among the modelling error, and the weight-update rule of multilayer neural network is derived to satisfy Laypunov stability. The whole control system constitutes controller using the feedback linearization method. The weight of neural network which is used to implement nonlinear function is updated by the derived update-rule. The proposed control algorithm is verified through computer simulation.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.227-236
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• 2005

Multibody system dynamics is based on classical mechanics and its engineering applications originating from mechanisms, gyroscopes, satellites and robots to biomechanics. Multibody system dynamics is characterized by algorithms or formalisms, respectively, ready for computer implementation. As a result simulation and animation are most convenient. Recent developments in multibody dynamics are identified as elastic or flexible systems, respectively, contact and impact problems, and actively controlled systems. Based on the history and recent activities in multibody dynamics, recursive algorithms are introduced and methods for dynamical analysis are presented. Linear and nonlinear engineering systems are analyzed by matrix methods, nonlinear dynamics approaches and simulation techniques. Applications are shown from low frequency vehicles dynamics including comfort and safety requirements to high frequency structural vibrations generating noise and sound, and from controlled limit cycles of mechanisms to periodic nonlinear oscillations of biped walkers. The fields of application are steadily increasing, in particular as multibody dynamics is considered as the basis of mechatronics.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.263-263
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• 2000

Electromagnetic Suspension(EMS) System produces no noise, friction and heat through non-contacting operation Therefore, the applicable device using EMS system has a lot of attraction in case of the high-speed and non-contacting transmission EMS with nonlinear properties requires a precise airgap position control and stable kinematics characteristics under the disturbances, In this study, the nonlinear system was linearized by a Nonlinear Feedback Lineariztion(NFL) method. The NFL method requires that the modelling should be exact, and the state variables should be measured and a rapidly operating controller be necessary on account of a heavy data calculating In the experiments. the ideal control characteristics of the NFL was acquired through simulation at first. then the characteristics of the actual system were compared with those of simulation. In addition, the results by NFL were examined and analysed considering the characteristics of the PID control. The Control by NFL shows much stable control characteristics than the PID control. Whereas, the steady state errors occur for various disturbances. hence a robust control design is remained for a further study.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.1
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• pp.42-47
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• 2003

Nonlinear models for a thin ring rotating at a constant speed are developed. The geometric nonlinearity of displacements is considered by adopting the Lagrange strain theory for the circumferential strain. By using Hamilton’s principle, the coupled nonlinear partial differential equations are derived, which describe the out-of-plane and in-plane bending, extensional and torsional motions. The natural frequencies are calculated from the linearized equations at various rotational speeds. Finally, the computation results from the nonlinear models are compared with those from a linear model. Based on the comparison, this study recommends which model is appropriate to describe the behavior of the rotating ring.

• Structural Engineering and Mechanics
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• v.30 no.4
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• pp.427-444
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• 2008

A mathematical model for the nonlinear dynamics of a rotating beam with flexible root attached to a rotating hub with elastic foundation is developed. The model is developed based on the large planar and flexural deformation theory and the potential energy method to account for axial shortening due to bending deformation. In addition the exact nonlinear curvature is used in the system potential energy. The Lagrangian dynamics and the assumed mode method is used to derive the nonlinear coupled equations of motion hub rotation, beam tip deflection and hub horizontal and vertical displacements. The derived nonlinear model is simulated numerically and the results are presented and discussed for the effect of root flexibility, hub stiffness, torque type, torque period and excitation frequency and amplitude on the dynamic behavior of the rotating beam-hub and on its stability.