• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.129-132
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• 1992

Cellular kinetics formulate the basis of tumor immune system dynamics which may be synthesized mathematically as cascades of bilinear systems which are connected by nonlinear dynamical terms. In this manner, a foundation for the control of syngeneic tumors is presented. We have analyzed the mechanisms of controlling the infiltration of lymphocytes into tumor tissues. Simulated anneal ins, a general-purpose method of multivariate optimization, is applied to combinatorial optimization, which is to find the minimum of a given function depending on many parameters. We compare the results of the different methods including the global optimization algorithm, known as simutated annealing.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.480-485
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• 2005

Perspective dynamical systems arise in machine vision problems, in which only perspective observation is available. This paper considers the state estimation problem for a rigid body moving in three dimensional spaces using the image data obtained by a CCD camera or some other means. Because the motion of the rigid body and the observed data are generally corrupted by noises, it is necessary to seek a state estimation method to reduce the influence of the noises. In this paper, by means of computer simulations for a simple example, we examine the sensitivity to the noises of the nonlinear observer developed in the recent paper ([1] R. Abdursul, H. Inaba and B. Ghosh, Nonlinear observers for perspective time-invariant linear systems, Automatica, vol. 40, Issue 3, pp. 481-490, 2004) and the effectiveness of the Extended Kalman Filter.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.5-8
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• 1999

The main stream of researches on the mobile robot is planning motions of the mobile robot under nonholonomic constraints while only considering kinematic model of a mobile robot. These researches, however, assume that there is some kind of dynamic controller which can produce perfectly the same velocity that is necessary for the kinematic controller. Moreover, there are little results about the problem of integrating the nonholonomic kinematic controller and the dynamic controller for a mobile robot. Also the literature on the robustness of the controller in the presence of uncertainties or external disturbances in the dynamical model of a mobile robot is very few. Thus, in this paper, the robust adaptive controller which can achieve velocity tracking while considering not only kinematic model but also dynamic model of the mobile robot is proposed. The stability of the dynamic system will be shown through the Lyapunov method.

• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.289-303
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• 2004

The non-rigid molecule group theory (NRG) in which the dynamical symmetry operations are defined as physical operations is a new field of chemistry. Smeyers in a series of papers applied this notion to determine the character table of restricted NRG of some molecules. In this work, a simple method is described, by means of which it is possible to calculate character tables for the symmetry group of molecules consisting of a number of NH3 groups attached to a rigid framework. We study the full non-rigid group (f-NRG) of tetraammineplatinum(II) with two separate symmetry groups C2v and C4v. We prove that they are groups of order 216 and 5184 with 27 and 45 conjugacy classes, respectively. Also, we will compute the character tables of these groups.

• Journal of the Korean Institute of Navigation
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• v.21 no.1
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• pp.109-118
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• 1997

In this paper, applications of multilayer neural networks to control of flexible robot beam are considered. The multilayer nerual networks can be used to approximate any continuous function to a desired degree of accuracy and the weights are updated by Gradient Method. When a flexible beam is rotated by a motor through the fixed end, transverse vibration may occur. The motor torque should be controlled insuch a way that the motor rotates by a specified angle, while simultaneously stabilizing vibration of the flexible manipulators so that is arrested as soon as possbile at the end of rotation. Accurate control of lightweight beam during the large changes in configuration common to robotic tasks requires dynamic models that describe both rigid body motions, as well as the flexural vibrations. Therefore, a linear dynamic state-space model of for a single link flexible robot beam is derived and PD controller, LQP controller, and inverse dynamical neural networks controller are composed. The effectiveness the proposed control system is confirmed by computer simulation.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2699-2701
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• 2000

This paper presents the Runge-Kutta neural networks(RKNN's) using the Runge-Kutta approximation method and the orthogonal function for control of unknown dynamical systems described by ordinary differencial equations in high accuracy. These subnetworks of RKNN's are based on orthogonal function. Computer simulations show the usefulness of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.2
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• pp.209-214
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• 1998

In this paper, we are dealing with the problem of controlling unknown nonlinear dynamical system by using neural networks. A novel error self-recurrent(ESR) neural model is presented to perform black-box identification. Through the various outcome of the experiment, a new neural network is seen to be considerably faster than the BP algorithm and has advantages of being less affected by poor initial weights and learning rate. These characteristics make it flexible to design the controller in real-time based on neural networks model. In addition, we design an adaptive PID controller that Keyser suggested by using ESR neural networks, and present a method on the implementation of adaptive controller based on neural network for practical applications. We obtained good results in the case of robot manipulator experiment.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.251-254
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• 1995

The Fuzzy-Neural Controller is constructed to resolve some dificulties taking place in decision of membership functions, input and output gains and an inferenced method for desinging fuzzy logic controller. In addition Neural network emulator is used to emulate induction motor forward dynamics and to get error signal at fuzzy-neural controller output layer. Error signal is backpropagated through neural network emulator. A back propagation algorithm is used to train fuzzy-neural controller and emulator. The experimental results show that this control system can provide good dynamical responses.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.45-67
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• 2021

In this paper, a mathematical dynamical system involving both deterministic (with or without delay) and stochastic "SIR" epidemic model with nonlinear incidence rate in a continuous reactor is considered. A profound qualitative analysis is given. It is proved that, for both deterministic models, if ��d > 1, then the endemic equilibrium is globally asymptotically stable. However, if ��d ≤ 1, then the disease-free equilibrium is globally asymptotically stable. Concerning the stochastic model, the Feller's test combined with the canonical probability method were used in order to conclude on the long-time dynamics of the stochastic model. The results improve and extend the results obtained for the deterministic model in its both forms. It is proved that if ��s > 1, the disease is stochastically permanent with full probability. However, if ��s ≤ 1, then the disease dies out with full probability. Finally, some numerical tests are done in order to validate the obtained results.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.91-97
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• 2014

Chaotic dynamics is an active research area in fields such as biology, physics, sociology, psychology, physiology, and engineering. Interest in chaos is also expanding to the social sciences, such as politics, economics, and societal events prediction. Most people pursue happiness, both spiritual and physical in many cases. However, happiness is not easy to define, because people differ in how they perceive it. Happiness can exist in mind and body. Therefore, we need to be happy in both simultaneously to achieve optimal happiness. To do this, we need to synchronize mind and body. In this paper, we propose a chaotic synchronization method in a mathematical model of happiness organized by a second-order ordinary differential equation with external force. This proposed mathematical happiness equation is similar to Duffing's equation, because it is derived from that equation. We introduce synchronization method from our mathematical happiness model by using the derived Duffing equation. To achieve chaotic synchronization between the human mind and body, we apply an idea of mind/body unity originating in Oriental philosophy. Of many chaotic synchronization methods, we use only coupled synchronization, because this method is closest to representing mind/body unity. Typically, coupled synchronization can be applied only to non-autonomous systems, such as a modified Duffing system. We represent the result of synchronization using a differential time series mind/body model.