• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.89-89
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• 2014

While the current consensus view holds that galaxy mergers are commonplace, it is sometimes speculated that Globular Clusters (GCs) may also have undergone merging events, possibly resulting in massive objects with a strong metallicity spread such as Omega Centauri. Galaxies are mostly far, unresolved systems whose mergers are most likely wet, resulting in observational as well as modeling difficulties, but GCs are resolved into stars that can be used as discrete dynamical tracers, and their mergers might have been dry, therefore easily simulated with an N-body code. It is however difficult to determine the observational parameters best suited to reveal a history of merging based on the positions and kinematics of GC stars, if evidence of merging is at all observable. To overcome this difficulty, we investigate the applicability of supervised and unsupervised machine learning to the automatic reconstruction of the dynamical history of a stellar system. In particular we test whether statistical clustering methods can classify simulated systems into monolithic versus merger products. We run direct N-body simulations of two identical King-model clusters undergoing a head-on collision resulting in a merged system, and other simulations of isolated King models with the same total number of particles as the merged system. After several relaxation times elapse, we extract a sample of snapshots of the sky-projected positions of particles from each simulation at different dynamical times, and we run a variety of clustering and classification algorithms to classify the snapshots into two subsets in a relevant feature space.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.753-757
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• 1994

In control system design, whether the various subsystems are in discrete time or continuous time, the state space is usually regarded as a continuum. However, when the system is implemented, some subsystems may have a state space which is a subset of finite computer arithmetic. This is an important concern if a subsystem has chaotic behaviour, because it is theoretically possible for rich and varied motions in a continuum to collapse to trivial and degenerate behaviour in a finite and discrete state space [5]. This paper discusses new ways to describe these effects and reports on computer experiments which document and illustrate such collapsing behaviour.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.705-713
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• 1999

In this paper, we propose a new motion and force control methodology for constrained robots as an approach of hybrid discrete-continuous dynamical system. The hybrid dynamic system modeling of robotic manipulation tasks with constraints is presented, and the hybrid system control architecture for unconstrained and constrained motion system with parametric uncertainties is synthesized. The optimal reference stiffness of robot manipulator is generated by the hybrid automata as a discrete state system and the control behavior of constrained system which has poor modeling information and time-varying constraint function is improved by the constrained robots as a continuous state system. The performance of the proposed constrained motion control system is successfully evaluated via experimental studies to the constraint tasks.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.667-672
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• 2003

In this paper, we propose a systematic method for intelligent digital redesign of a fuzzy-model-based controller for continuous-time nonlinear dynamical systems which may also contain uncertainties. The continuous-time uncertain TS fuzzy model is first constructed to represent the uncertain nonlinear systems. An extended parallel distributed compensation(EPDC) technique is then used to design a fuzzy-model-based controller for both stabilization and tracking. The designed continuous-time controller is then converted to an equivalent discrete-time controller by using an integrated intelligent digital redesign method. This new design technique provides a systematic and effective framework for integration of the fuzzy-model-based control theory and the advanced digital redesign technique for nonlinear dynamical systems with uncertainties. Finally, The single link flexible-joint robot arm is used as an illustrative example to show the effectiveness and the feasibility of the developed design method.

• Communications of the Korean Mathematical Society
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• v.34 no.3
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• pp.967-979
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• 2019

Chaotic dynamical systems, preferably on a Cantor-like space with some arithmetic operations are considered as good pseudo-random number generators. There are many definitions of chaos, of which Devaney-chaos and pos itive topological entropy seem to be the strongest. Let $A=\{0,1,{\dots},p-1\}$. We define a continuous map on $A^{\mathbb{Z}}$ using addition with a carry, in combination with the shift map. We show that this map gives rise to a dynamical system with positive entropy, which is also Devaney-chaotic: i.e., it is transitive, sensitive and has a dense set of periodic points.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.81-84
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• 2000

Cellular automata are discrete dynamical systems whose behaviour is completely specified in terms of a local relation. If cellular automata convergence to fixed points, then it can be used to image processing. From the generalized Potts automata point of view, we propose in this paper a cellular automata technique for reducing image noise. To minimize blurring effect, an algorithm based on neighborhood median computation is Preferred. Experimental results are reported.

• Journal of KSNVE
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• v.10 no.4
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• pp.610-614
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• 2000

Cellular Automata(CA)s are used as a simple mathematical model to investigate self-organization in statistical mechanics, which are originally introduced by von Neumann and S. Ulam at the end of the 1940s. CAs provide a framework for a large class of discrete models with homogeneous interactions, which are characterized by the following fundamental properties: 1) CAs are dynamical systems in which space and time are discrete. 2) The systems consist of a regular grid of cells. 3) Each cell is characterized by a state taken from a finite set of states and updated synchronously in discrete time steps according to a local, identical interaction rule. 4) The state of a cell is determined by the previous states of a surrounding neighborhood of cells. A cellular automaton has been attracted wide interest in modeling physical phenomena, which are described generally, partial differential equations such as diffusion and wave propagation. This paper describes one and two-dimensional analysis of wave propagation phenomena modeled by CA, where the local interaction rules were derived referring to the Lattice Gas Model reported by Chen et al., and also including finite difference scheme. Modeling processes by using CA are discussed and the simulation results of wave propagation with one wave source are compared with that by finite difference method.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.231-236
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• 1997

We propose the hybrid control for the path control of wheeled mobile robot system. To develop the hybrid control of mobile robot, the continuous dynamics of mobile robot are modeled by the switched systems. The abstract model and digital automata for the path control are developed. This hybrid control system has the 3-layered hierachical structure : digital automata as the higher process, mobile robot system as the lower process, and the interface as the interaction process between the continuous dynamics and the discrete dynamics. The control of following the desired-paths with edges are investigated as the applications by the computer simulation.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.169-174
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• 2000

In this paper, Haar wavelet-based neural network is described for the identification and control of discrete-time nonlinear dynamical systems. Wavelets are suited to depict functions with local nonlinearities and fast variations because of their intrinsic properties of finite support and self-similarity. Due to the orthonormal properties of Haar wavelet functions, wavelet neural networks result in a greatly simplified training problem. This wavelet-based scheme performs adaptively both the identification of nonlinear functions and the control of the overall system, while the multilayer neural network is applied to the control system just after its sufficient learning of the unknown functions. Simulation shows that the wavelet network can be a good alternative to a multilayer neural network with backpropagation.

• Journal of Computing Science and Engineering
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• v.3 no.2
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• pp.73-87
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• 2009

A hybrid system is a dynamical system in which states can be changed continuously and discretely. Simulation based on numerical methods is the widely used technique for analyzing complicated hybrid systems. Numerical simulation of hybrid systems, however, is subject to two types of numerical errors: truncation error and round-off error. The effect of such errors can make an impossible transition step to become possible during simulation, and thus, to generate a simulation behavior that is not allowed by the model. The possibility of an incorrect simulation behavior reduces con.dence in simulation-based analysis since it is impossible to know whether a particular simulation trace is allowed by the model or not. To address this problem, we define the notion of Instrumented Hybrid Automata (IHA), which considers the effect of accumulated numerical errors on discrete transition steps. We then show how to convert Hybrid Automata (HA) to IRA and prove that every simulation behavior of IHA preserves the discrete transition steps of some behavior in HA; that is, simulation of IHA is sound with respect to HA.