• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.670-683
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• 2016

Network coding, as a new technique to improve the throughput, is studied combined with multi-relay model in this paper to address the challenges of long distance and power limit in deep space communication. First, an amplify-and-forward relaying approach based on analog network coding (AFNC) is proposed in multi-relay network to improve the capacity for deep space communication system, where multiple relays are introduced to overcome the long distance link loss. The design of amplification coefficients is mathematically formulated as the optimization problem of maximizing SNR under sum-power constraint over relays. Then for a dual-hop relay network with a single source, the optimal amplification coefficients are derived when the multiple relays introduce non-coherent noise. Through theoretic analysis and simulation, it is shown that our approach can achieve the maximum transmission rate and perform better over single link transmission for deep space communication.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.431-441
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• 1991

A robust H$_{\infty}$ control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multi-parameter variations in the state-space formulation of H$_{\infty}$ control theory. An application of this robust H$_{\infty}$ control synthesis technique to the Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73% in one of the structured uncertainty directions. The performance and stability of this new robust H$_{\infty}$ controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.que.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.103-112
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• 2007

This paper presents a practical approach for surface reconstruction from unoriented point clouds. Instead of estimating local surface orientation, we first generate a set of depth images from the input point clouds, and a coarse mesh is then generated based on them by space carving techniques. The resultant mesh is progressively refined by local mesh refinement and optimization according to surface distance measure. A manifold mesh approximating the input points within an given tolerance is finally obtained. Our approach is easy to implement, but has the ability to outputs high quality meshes in different resolutions. We show that the proposed approach is not sensitive to several types of data disfigurement and is able to reconstruct models robustly from variance input data.

• Journal of Computing Science and Engineering
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• v.9 no.1
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• pp.9-19
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• 2015

The most important challenge in the region-based abstraction method as an approach to compute the state space of time Petri Nets (TPNs) for model checking is that the method results in a huge number of regions, causing a state explosion problem. Thus, region-based abstraction methods are not appropriate for use in developing practical tools. To address this limitation, this paper applies a modification to the basic region abstraction method to be used specially for computing the state space of TPN models, so that the number of regions becomes smaller than that of the situations in which the current methods are applied. The proposed approach is based on the special features of TPN that helps us to construct suitable and small region graphs that preserve the time properties of TPN. To achieve this, we use TPN-TCTL as a timed extension of CTL for specifying a subset of properties in TPN models. Then, for model checking TPN-TCTL properties on TPN models, CTL model checking is used on TPN models by translating TPN-TCTL to the equivalent CTL. Finally, we compare our proposed method with the current region-based abstraction methods proposed for TPN models in terms of the size of the resulting region graph.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.4
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• pp.97-109
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• 1998

In this paper, we propose a new approach to solve stochastic fluid flow models applied to the analysis of ceil loss of an ATM multiplexer. Existing stochastic fluid flow models have been analyzed by using linear differential equations. In case of large state space, however. analyzing stochastic fluid flow model without numerical errors is not easy. To avoid this numerical errors and to analyze stochastic fluid flow model with large state space. we develope a new computational algorithm. Instead of solving differential equations directly, this approach uses iterative and numerical method without calculating eigenvalues. eigenvectors and boundary coefficients. As a result, approximate solutions and upper and lower bounds are obtained. This approach can be applied to stochastic fluid flow model having general Markov chain structure as well as to the superposition of heterogeneous ON-OFF sources it can be extended to Markov process having non-exponential sojourn times.

• Structural Engineering and Mechanics
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• v.59 no.1
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• pp.101-122
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• 2016

Elasticity solutions for bi-directional functionally graded beams subjected to arbitrary lateral loads are conducted, with emphasis on the end effects. The material is considered macroscopically isotropic, with Young's modulus varying exponentially in both axial and thickness directions, while Poisson's ratio remaining constant. In order to obtain an exact analysis of stress and displacement fields, the symplectic analysis based on Hamiltonian state space approach is employed. The capability of the symplectic framework for exact analysis of bi-directional functionally graded beams has been validated by comparing numerical results with corresponding ones in open literature. Numerical results are provided to demonstrate the influences of the material gradations on localized stress distributions. Thus, the material properties of the bi-directional functionally graded beam can be tailored for the potential practical purpose by choosing suitable graded indices.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1341-1345
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• 2005

Sequential Monte Carlo techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation in nonlinear non-Gaussian state-space models. We can use Monte Carlo particle filters adaptively, i.e. so that they simultaneously estimate the parameters and the signal. However, Sequential Monte Carlo techniques require the use of special panicle filtering techniques which suffer from several drawbacks. We consider here an alternative approach combining particle filtering and Sequential Hybrid Monte Carlo. We give some examples of applications in fisheries(luespotted mud hopper data).

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.6
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• pp.765-771
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• 1998

An artificial neural network(NN) technique is developed for hardware redundant sensor validation. Since the measurement space is a continuous space with many operating regions, it is difficult to train a NN to correctly detect failure in an accurate measurement system. A conventional backpropagation NN is modified to include an additional preprocessing layer that extracts classification features from scalar measurements. This feature extraction means transform the measurement space to parity space. The NN is independent of the state variable being measured, the instrument range, and the signal tolerance. This NN resembles the parity space approach to signal validation, except that analytical parity equations are unneeded and the NN pattern recognition capability is utilized for decision making.

• International Journal of Aeronautical and Space Sciences
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• v.12 no.1
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• pp.43-56
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• 2011

An integrated system composed of guidance, navigation and control (GNC) system for autonomous proximity operations and the docking of two spacecraft was developed. The position maneuvers were determined through the integration of the state-dependent Riccati equation formulated from nonlinear relative motion dynamics and relative navigation using rendezvous laser vision (Lidar) and a vision sensor system. In the vision sensor system, a switch between sensors was made along the approach phase in order to provide continuously effective navigation. As an extension of the rendezvous laser vision system, an automated terminal guidance scheme based on the Clohessy-Wiltshire state transition matrix was used to formulate a "V-bar hopping approach" reference trajectory. A proximity operations strategy was then adapted from the approach strategy used with the automated transfer vehicle. The attitude maneuvers, determined from a linear quadratic Gaussian-type control including quaternion based attitude estimation using star trackers or a vision sensor system, provided precise attitude control and robustness under uncertainties in the moments of inertia and external disturbances. These functions were then integrated into an autonomous GNC system that can perform proximity operations and meet all conditions for successful docking. A six-degree of freedom simulation was used to demonstrate the effectiveness of the integrated system.

• Journal of Electrical Engineering and Technology
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• v.6 no.5
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• pp.697-705
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• 2011

In this paper, a closed-loop system constructed with a linear plant and nonlinearity in the feedback connection is considered to argue against its planar orbital stability. Through a state space approach, a main result that presents a sufficient stability criterion of the limit cycle predicted by solving the harmonic balance equation is given. Preliminarily, the harmonic balance of the nonlinear feedback loop is assumed to have a solution that determines the characteristics of the limit cycle. Using a state-space approach, the nonlinear loop equation is reformulated into a linear perturbed model through the introduction of a residual operator. By considering a series of transformations, such as a modified eigenstructure decomposition, periodic averaging, change of variables, and coordinate transformation, the stability of the limit cycle can be simply tested via a scalar function and matrix. Finally, the stability criterion is addressed by constructing a composite Lyapunov function of the transformed system.