• 한국전산유체공학회:학술대회논문집
• /
• 2006.10a
• /
• pp.159-162
• /
• 2006

In the microfluidics devices the most important thing is mixing efficiency of various fluids. In this study a newly designed mixer is proposed to enhance the mixing effect with the purpose to apply it to microchannel mixing in a short future. This design is composed of a channel with cross baffles periodically arranged on the both bottom and top surfaces of the channel. To obtain the flow patterns, the numerical computation was performed by using a commercial code, ANSYS CFX 10.0. To evaluate the mixing performance, we computed Lyapunov exponent and obtained Poincare sections.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1992.10a
• /
• pp.215-219
• /
• 1992

This paper presents a motion coordination of two robot manipulators coordinating an object. To coordinate the object, a force/position control scheme in a mode of leaer/follower is devised. The dynamics of the object are incorporated into the dynamics of the leader arm, which yields a reduced order model of two arm system. In order to regulate interaction forces between two arm, the dynamics of the follower arm are expressed as force dynamic equations such that a novel direct forces between two arms and two different type of bounded input disturbances, boundedness and asymptotic stability results based on a proposed Lyapunov function are shown. Also, a sufficient condition for a stability robustness is derived based on the Lyapunov approach.

• Proceedings of the Korean Society of Marine Engineers Conference
• /
• 2006.06a
• /
• pp.85-86
• /
• 2006

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundary function is proposed and applied to a two-wheeled voiding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the new sliding is proposed to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system will be shown through the Lyapunov method. The simulations is shown to prove the effectiveness of the proposed controller.

• Journal of Mechanical Science and Technology
• /
• v.17 no.12
• /
• pp.1994-2003
• /
• 2003

The vibration of a flexible cantilever tube with nonlinear constraints when it is subjected to flow internally with fluids is examined by experimental and theoretical analysis. These kinds of studies have been performed to find the existence of chaotic motion. In this paper, the important parameters of the system leading to such a chaotic motion such as Young's modulus and the coefficient of viscoelastic damping are discussed. The parameters are investigated by means of system identification so that comparisons are made between numerical analysis using the design parameters and the experimental results. The chaotic region led by several period-doubling bifurcations beyond the Hopf bifurcation is also re-established with phase portraits, bifurcation diagram and Lyapunov exponent so that one can define optimal parameters for system design.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2003.04a
• /
• pp.305-311
• /
• 2003

We propose a new technique of adaptive-neuro controller design to implement real-time control of robot manipulator, Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of loaming a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real time control of robot system using DSPs(TMS320C50)

• Journal of Industrial Technology
• /
• v.3
• /
• pp.3-8
• /
• 1983

미분방정식(微分方程式)으로 주어지는 높은 차수(次數)의 동특성(動特性) 시스템의 안정도(安定度)를 Lyapunov 이론(理論)을 이용(利用)하여 해석(解析)하였다. 대규모(大規模) 시스템 자체(自體)를 직접(直接) 해석(解析)함에 있어서는 그의 복잡성(複雜性)과 차수문제(次數問題)가 대두(擡頭)되어 매우 곤란하다. 따라서 가능(可能)한(限) 보다 작은 차수(次數)의 시스템으로 분할(分割)하여 해석(解析)하고 이를 다시 합성(合成)하여 종합(綜合) 해석(解析)하였으며 분할(分割)된 작은 차수(次數)의 시스템에 대해서는 수학행렬(數學行列)의 안정특성(安定特性)을 이용(利用)한 새로운 형태(形態)의 Lyapunov 함수(函數)를 사용(使用)하였다. 응용(應用)의 한 예(例)로써, 3개(個)의 동기발전기(同期發電機)를 가진 전력계통(電力系統)에 적용(適用)하여 기존(旣存)의 방법(方法)보다 용역(容易)하게 이 시스템의 안정도(安定度)를 판별(判別)할 수 있었다.

• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.271-274
• /
• 1995

This paper is concerned with the problem of robust stabilization of uncertain single-input and single-output nonlinear systems. Based on the input/output linearization approach for nonlinear state feedback synthesis in conjunction with Lyapunov methods, a stabilizing state feedback controller is proposed. Compared with the controllers reported in the control literature, instead of uniform ultimate boudedness, the controller proposed in this paper can guarantee uniform asymptotic stability of nonlinear systems in the presence of uncertainties. The required information about uncertain dynamics in the system is only that the uncertainties are bounded in Euclidean norm by known functions of the system state.

• Journal of Institute of Control, Robotics and Systems
• /
• v.2 no.3
• /
• pp.142-147
• /
• 1996

In this paper, we describe the algorithm which controls an unknown nonlinear system with 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 unknown nonlinear function on the nonlinear system by using of multilayer neural network. The weight-update rule of multilayer neural network is derived to satisfy Lyapunov stability. The whole control system constitutes controller using 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 Institute of Control, Robotics and Systems
• /
• v.2 no.3
• /
• pp.158-164
• /
• 1996

In this paper, we consider the problem of robust stability of discretd time-delay systems subjected to perturbations. Two classes of perturbations are treated. The first one is the nonlinear norm-bounded perturbation, and the second is the structured time-varying parametric perturbation. Based on the discrete-time Lyapunov stability theory, several new sufficient conditions for robust stability of the system are presented. From these conditions, we can estimate the maximum allowable bounds of the perturbations which guarantee the stability. Finally, numerical examples are given to demonstrate the effectiveness of the results.

• Journal of Institute of Control, Robotics and Systems
• /
• v.5 no.7
• /
• pp.794-799
• /
• 1999

This study deals with robustness bounds estimation for uncertain linear systems with structured perturbations where the eigenvalues of the perturbed systems are guaranteed to stay in a prescribed region. Based upon the Lyapunov approach, new theorems to estimate allowable perturbation parameter bounds are derived. The theorems are referred to as the zero-order or first-order asymmetric robustness measure depending on the order of the P matrix in the sense of Taylor series expansion of perturbed Lyapunov equation. It is proven that Gao's theorem for the estimation of stability robustness bounds is a special case of proposed zero-order asymmetric robustness measure for eigenvalue assignment. Robustness bounds of perturbed parameters measured by the proposed techniques are asymmetric around the origin and less conservative than those of conventional methods. Numerical examples are given to illustrate proposed methods.