• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.10
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• pp.1287-1292
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• 1999

In large-scale systems, we frequently encounter the time-delay and the uncertainty, and these should be considered in the design of controller because these are the source of the degradation of the system performance and instability of system. In this paper, we consider the robust stability of the linear large scale systems with the uncertainties and the time-delays. The considered uncertainties are both structured uncertainty and the unstructured uncertainty. Also, the considered time-delays are time-varying having finite time derivative limits. Based on the Lyapunov theorem and the linear matrix inequality(LMI) technique, we present two sufficient conditions that guarantee the robust stability of the system. The conditions are expressed as the LMI forms which can be easily checked their feasibility by using the well-known LMI control toolbox. Finally, we show by two examples that our results are less conservative than the previous results.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.394-396
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• 2005

In this paper, we propose an adaptive tracking control method of a mobile manipulator for contour following with a kinematic model to have several unknown dimension parameters. Moreover, we will use the decentralized control method to design two independent controllers for two subsystems. The proposed controllers in this paper are based on the Lyapunov function in order to guarantee the stability of whole system for contour following task. The updated laws are also designed to estimated the unknown dimension parameters. Finally, the simulation results are presented to show the validity of the proposed controllers in this paper.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.161-163
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• 2005

This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems are used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system. we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem. and convergence and robustness properties are demonstrated. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.2
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• pp.189-199
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• 1999

This paper presents an optimization algorithm for a stable Self Dynamic Neural Network(SDNN) using genetic algorithm. Optimized SDNN is applied to a problem of controlling nonlinear dynamical systems. SDNN 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. SDW has considerably fewer weights than DNN. Since there is no interlink among the hidden layer. The object of proposed algorithm is that 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.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.401-406
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• 2012

This paper considers multi-agent systems with interval time-varying delays and switching interconnection topology. By construction of a suitable Lyapunov-Krasovskii's functional, new delay-dependent consensus control conditions for the systems are established in terms of LMIs (Linear Matrix Inequalities) which can be easily solved by various effective optimization algorithms. One numerical example is given to illustrate the effectiveness of the proposed methods.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.6
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• pp.513-518
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• 2012

In this paper, we propose a generalized index independent stability condition for a descriptor systemwithout any transformations of system matrices. First, the generalized Lyapunov equation with a specific right-handed matrix form is considered. Furthermore, the existence theorem and the necessary and sufficient conditions for asymptotically stable descriptor systems are presented. Finally, some suitable examples are used to show the validity of the proposed method.

• Journal of applied mathematics & informatics
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• v.26 no.5_6
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• pp.961-972
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• 2008

In this paper, we consider the global exponential stability of cellular neural networks with time-varying delays. Based on the Lyapunov function method and convex optimization approach, a novel delay-dependent criterion of the system is derived in terms of LMI (linear matrix inequality). In order to solve effectively the LMI convex optimization problem, the interior point algorithm is utilized in this work. Two numerical examples are given to show the effectiveness of our results.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.49-55
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• 2007

The quality of chaotic mixing in three-dimensional micro channel flow has been numerically studied using Fractional-step method (FSM) and particle tracking techniques such as $Poincar{\acute{e}}$ section and Lyapunov exponents. The flow was driven by pressure distribution and the chaotic mixing was generated by applying alternating current to electrodes embedded on the bottom wall at a first half period and on the top wall at a second half period. The equations governing the velocity and concentration distributions were solved using FSM based on Finite Volume approach. Results showed that the mixing quality depended significantly on the modulation period. The modulation period for the best mixing performance was determined based on the mixing index for various initial conditions of concentration distribution. The optimal values of modulation period obtained by the particle tracking techniques were compared with those from the solution of concentration distribution equation using FSM and CFX software and the comparison showed their good match.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.219-226
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• 2003

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory fir the adaptive control of linear systems, there exists relatively little general theory fir the adaptive control of nonlinear systems. Adaptive control technique is essential fir providing a stable and robust performance fir application of robot control. The proposed neuro control algorithm is one of teaming 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 f3r real-time control of robot system using DSPs.

• Journal of computational fluids engineering
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• v.11 no.4 s.35
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• pp.101-106
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• 2006

In the microfluidic devices the most important thing is mixing efficiency ol various fluids. In this study a newly designed miler 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 ol the channel. To obtain the yow 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. it was shown that our design provides the excellent mixing effect.