In this paper, the goal is to obtain a dynamic model of a particular system. The system is a combination of a wheeled vehicle(chassis) with a turret rotating in azimuth direction and a gun rotating in a elevation direction. At this time, the motion of the gun according to the shaking of the continuous shot is obtained using the coordinate transformation equation in the azimuth and elevation angle. Also, the dynamic model for the swaying of wheeled vehicle is obtained through the Lagrange’s equation. Through this, we analyze the tumbles of the gun, whiat is the major term, and what dynamics are needed for stabilization control.

본 연구에서는 비소 오염 토양의 안정화소재로서 주로 사용되고 있지만 그 품질관리가 어려운 제강슬래그의 재료적 특성을 파악하기 위한 기초적인 실험을 수행하였다. 제강슬래그의 입도에 따른 화학적 성질의 변화와 비소 안정화에 중요한 성분인 Fe 성분의 입도에 따른 용출특성 그리고 제강슬래그의 주요 성분인 철(Fe)과 칼슘(Ca) 성분의 구성 비율이 비소의 흡착에 미치는 영향 등에 대해서 흡착실험을 실시하여 관찰하였다. 제강슬래그의 입도는 화학적 성질에 영향을 주지는 못하는 것으로 나타났다. 그러나 용출은 입도가 작은 분말상태에서 높게 나타났으나 pH=2 조건에서만 용출이 발생되어 실제 자연상태에서 용출이 일어나기는 어려울 것으로 판단되었다. 철과 칼슘성분의 혼합비에 따른 비소의 흡착실험에서는 철과 칼슘이 일정비율 섞여 있는 경우에서 효과가 매우 우수한 것으로 나타났으며, 철이나 칼슘 성분 모두 25%이상만 혼합되면 비슷한 효과를 나타내는 것으로 보인다. 한편 칼슘만 존재하는 경우에는 초기의 효과는 높았으나 시간이 경과하면서 재용출 현상이 나타나 적당하지 않은 것으로 나타났으며, 철 성분만 사용한 경우에는 초기 효과는 낮았으나 시간이 경과하면서 흡착효과가 지속적으로 증가하는 것으로 나타나 장기효과가 높을 것으로 기대되었다.

Mordern Ocean-going ships utilize stabilization techniques in order to minimize the effects of oscillations due to the unwanted disturbances. In this paper, as an elementary design of automatic control system with linear-state vari;tble feedback and series compensator for ship stabilization, analysis and design is limited to the linear time-invariant single input and output system. In order for the Controlled system to meet the requirements of stability, accuracy and transient response, a model of the automatic control system is proposed. For the analysis and design of this model, the state-space method, that is, the mordern way, or an alternative to the transfer function method of describing a linear system that utilize the state variables and state equations, is applied.

This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.