• 수산해양기술연구
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• 제56권1호
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• pp.61-70
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• 2020

In this study, system modeling and dynamic analysis of crane are conducted. Especially, among many different kinds of a crane system, the issues on crane operating problems installed on the vessel are considered. As well known, marine systems including cranes are exposed to various disturbances such as vessel motions, hydrodynamic forces, wave and wind attack, etc. In order to analysis the system dynamic with environmental conditions, the authors derived the nonlinear dynamic model of offshore crane and derived a linear model which is used for designing the control system. Using the obtained nonlinear and linear models, simulations were conducted to evaluate the usefulness of the obtained models. By simulation and result evaluation, the usefulness of the linear model, which presents the dynamics, is effectively verified.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.600-605
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• 2001

This paper deals with dynamic performance of the Cheju - Haenam HVDC system. The purpose of the study is to verify the control characteristics of the HVDC system and to analyze the dynamic performances by simulation study. Because the HVDC system consists of analogue and digital controller, the simulation is achieved with specification model incorporating nonlinear function. The dynamic performance simulations are performed by PSCAD/EMTDC

• 전자공학회논문지S
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• 제35S권7호
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• pp.103-108
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• 1998

In this paper, we atempt to control the nonlinear power system for resistance spot welders to be a fully linearizesd system by applying the recently developed nonlinear feedback linearization techniques. the controller proposed in this paper is computationally simple. In addition, the easy gain tuning as well as the high dynamic performance of resistance spot welding systems can be obained simulaneously. To illustrate the dynamic performance of our controller further, we present some simulation results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.437-440
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• 1988

This paper discuss which new dynamic control method for robot arm. It is basedon nonlinear feedback and T transformation which externally linearizes the whole system and provides simultaneous output decoupling. The nonlinear feedback augmented with optimal error correcting controller, which operates on the task error level. Computer simulation were appled to evaluate the performance of new dynamic control method. The simulation results are discussed in detail.

• Interaction and multiscale mechanics
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• 제3권4호
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• pp.309-320
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• 2010

With taking the geometric nonlinearity of bridge structure into account, a framework is presented for predicting the dynamic responses of a long-span suspension bridge subjected to running train and turbulent wind. The nonlinear dynamic equations of the coupled train-bridge-wind system are established, and solved with the Newmark numerical integration and direct interactive method. The corresponding linear and nonlinear processes for solving the system equation are described, and the corresponding computer codes are written. The proposed framework is then applied to a schemed long-span suspension bridge with the main span of 1120 m. The whole histories of the train passing through the bridge under turbulent wind are simulated, and the dynamic responses of the bridge are obtained. The results demonstrate that the geometric nonlinearity does not influence the variation tendency of the bridge displacement histories, but the maximum responses will be changed obviously; the lateral displacement of bridge are more sensitive to the wind than the vertical ones; compared with wind velocity, train speed affects the vertical maximum responses a little more clearly.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.740-743
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• 1998

This paper presents an optimization algorithm for a stable Dynamic Neural Network (DNN) using genetic algorithm. Optimized DNN is applied to a problem of controlling nonlinear dynamical systems. DNN is dynamic mapping and is better suited for dynamical systems than static forward neural network. The real time implementation is very important, and thus the neuro controller also needs to be designed such that it converges with a relatively small number of training cycles. SDNN has considerably fewer weights than DNN. The object of proposed algorithm is to the number of self dynamic neuron node and the gradient of activation functions are simultaneously optimized by genetic algorithms. To guarantee convergence, an analytic method based on the Lyapunov function is used to find a stable learning for the SDNN. The ability and effectiveness of identifying and controlling, a nonlinear dynamic system using the proposed optimized SDNN considering stability' is demonstrated by case studies.

• International Journal of Precision Engineering and Manufacturing
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• 제3권1호
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• pp.66-75
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• 2002

The crane operation used fur transporting heavy loads causes a swinging motion with the loads due to the crane\`s acceleration and deceleration. This sway causes the suspension ropes to leave their grooves and can cause serious damage. Ideally, the purpose of a crane system is to transport loads to a goal position as soon as possible without any oscillation of the rope. Currently, cranes are generally operated based on expert knowledge alone, accordingly, the development of a satisfactory control method that can efficiently suppress object sway during transport is essential. The dynamic behavior of a crane shows nonlinear characteristics. When the length of the rope is changed, a crane becomes a time-varying system thus the design of an anti-sway controller is very difficult. In this paper, a nonlinear dynamic model is derived for an industrial overhead crane whose girder, trolley, and hoister move simultaneously. Furthermore, a fuzzy logic controller, based on expert experiments during acceleration, constant velocity, deceleration, and stop position periods is proposed to suppress the swing motion and control the position of the crane. Computer simulation is then used to test the performance of the fuzzy controller with the nonlinear crane model.

• 한국정밀공학회지
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• 제16권8호
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• pp.193-202
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• 1999

Crane operation for transporting heavy loads causes swinging motion at the loads due to crane's acceleration and deceleration. This sway causes the suspension ropes to leave their grooves and leads to possibility of serious damages. So, this swing of the objects is a serious problem and the goal of crane system is transporting to a goal position as soon as possible without the oscillation of the rope. Generally crane is operated by expert's knowledge. Therefore, a satisfactory control method to supress object sway during transport is indispensible. The dynamic behavior of the crane shows nonlinear characteristics. when the length of the rope is changed the crane is time varying system and the design of anti-sway controller is very difficult. In this paper, the nonlinear dynamic model for the industrial overhead crane whose girder, trolley and hoister move simultaneously is derived. and the Fuzzy logic controller based on the expert experiments during acceleration, constant velocity, deceleration and stop position period is proposed to supress the swing motion and control the position of the crane. The performance of the fuzzy controller for the nonlinear crane model is simulated on the personal computer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2006년도 심포지엄 논문집 정보 및 제어부문
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• pp.219-221
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• 2006

The recently developed autopilot controller can make the input-output (I/O) dynamic characteristics of the nonlinear missile dynamics linear and independent of flight conditions. However, significant fin actuator dynamics can degenerate the I/O dynamic performance of the overall system. In this paper, we propose a singular perturbation-like method to compensate the effect of significant fin actuator dynamics in nonlinear missile control. The proposed compensation method does not require the time derivatives of fin angles but can maintain the linear I/O dynamic characteristics provided by the recently developed autopilot controller.

• International Journal of Control, Automation, and Systems
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• 제1권2호
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• pp.215-221
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• 2003

The education system in this paper is used to demonstrate and educate the effects of electromagnetic induction. Placing an aluminum ring over the core and switching on AC source causes the ring to jump in the air due to induced currents in the ring producing a magnetic field opposed to that produced in the core. To control the position of the ring by only the current, it is to require nonlinear control algorithm and control board that is composed of photo sensors, decode circuit, computer communication, and power electronics circuit. This paper provides the development for education system in detail and the effects of dynamic neural networks for nonlinear control with on line is studied.