• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.5
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• pp.408-415
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• 2011

The moon landing is composed of the de-orbit descent phase, powered descent phase, and the powered descent phase is divide into 3-sub phase of the braking, approach, final landing phase. In this paper, the lunar lander perform landing control using 3-sub phase of optimal trajectory. First, generate the reference trajectory using gauss pseudo-spectral method. Thereafter generate PID controller using altitude and velocity error in each direction. Finally the lunar lander landing system constitute using the Simulink of Matlab, and perform simulation.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.12
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• pp.1184-1194
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• 2010

The descent and ascent phases for a lunar lander are composed of several phases. Accordingly, the constraints and control values adequate for each phase are required in order to generate optimal lander's trajectory. The optimal trajectories for descent and ascent phases are generated by the cost function to minimize fuel consumption & attitude variation rates. In this paper, the optimal control problem to make trajectory uses Gauss pseudo-spectral method which is one of the direct approach method. This problem generates lander's reference trajectory, states and controls.

• Journal of Applied and Pure Mathematics
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• v.5 no.3_4
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• pp.129-164
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• 2023

The aim of this work is to present some interesting results on weighted ergodic functions and prove the existence and uniqueness of Stepanov-like pseudo almost automorphic solutions using the spectral decomposition of the phase space developed by Adimy and co-authors. We also give the next challenge of this work.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.28 no.11
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• pp.1398-1406
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• 2004

The nonlinear signals from an impedance meter for the area average void fraction in two-phase flow have been analyzed to construct a phase space trajectory. The pseudo phase space was constructed with the time delay and proper dimensions. The time delay and the embedding dimension were chosen by the average mutual information and by the false nearest neighborhood, respectively. The attractor-density-map of projected states was used to produce the two dimensional probability distribution functions (2D-PDF). Since the developed 2D-PDF showed clear distinction of the flow patterns, the flow regime identification was made with three rules and with the 2D-PDF. Also, the transition criteria of Mishima-Ishii agree well with the present results.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.1-13
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• 2020

To give a solution for seismic stability of tunnel faces subjected to earthquake ground shakings, the pseudo-dynamic approach is originally introduced to analyze tunnel face stability in this study. In the light of the upper-bound theorem of limit analysis, an advanced three-dimensional mechanism combined with pseudo-dynamic approach is proposed. Based on this mechanism, the required support pressure on tunnel face can be obtained by equaling external work rates to the internal energy dissipation and implementing an optimization searching procedure related to time. Both time and space feature of seismic waves are properly accounted for in the proposed mechanism. For this reason, the proposed mechanism can better represent the actual influence of seismic motion and has a remarkable advantage in evaluating the effects of vertical seismic acceleration, soil amplification factor, seismic wave period and initial phase difference on tunnel face stability. Furthermore, the pseudo-dynamic approach is compared with the pseudo-static approach. The difference between them is illustrated from a new but understandable perspective. The comparison demonstrates that the pseudo-static approach is a conservative method but still could provide precise enough results as the pseudo-dynamic approach if the value of seismic wavelengths is large or the height of soil structures is small.

• International Journal of Aeronautical and Space Sciences
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• v.14 no.1
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• pp.67-74
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• 2013

Nonlinear guidance law combined with a pseudo pursuit guidance is proposed, to perform stationary target observation mission. Multiple UAVs are considered, with waypoint constraint. The whole guidance is divided into two steps: firstly, waypoint approach, with specified incidence angle; and secondly, loitering around the stationary target. Geometric approach is used to consider the constraint on the waypoint, and a specified phase angle between the loitering UAV and the approaching UAV. In the waypoint approach step, UAVs fly to the waypoint using the pseudo pursuit guidance law. After passing the waypoint, UAVs turn around the target, using a distance error dynamics-based guidance law. Numerical simulations are performed, to verify the performance of the proposed guidance law.

• Journal of Astronomy and Space Sciences
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• v.26 no.1
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• pp.59-74
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• 2009

Relative navigation system is presented using GPS measurements from a single-channel global positioning system (GPS) simulator. The objective of this study is to provide the real-time inter-satellite relative positions as well as absolute positions for two formation flying satellites in low earth orbit. To improve the navigation performance, the absolute states are estimated using ion-free GRAPHIC (group and phase ionospheric correction) pseudo-ranges and the relative states are determined using double differential carrier-phase data and singled-differential C/A code data based on the extended Kalman filter and the unscented Kalman filter. Furthermore, pseudo-relative dynamic model and modified relative measurement model are developed. This modified EKF method prevents non-linearity of the measurement model from degrading precision by applying linearization about absolute navigation solutions not about the priori estimates. The LAMBDA method also has been used to improve the relative navigation performance by fixing ambiguities to integers for precise relative navigation. The software-based simulation has been performed and the steady state accuracies of 1 m and 6 mm ($1{\sigma}$ of 3-dimensional difference errors) are achieved for the absolute and relative navigation using EKF for a short baseline leader/follower formation. In addition, the navigation performances are compared for the EKF and the UKF for 10 hours simulation, and relative position errors are mm-level for the two filters showing the similar trends.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.218-223
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• 2008

A new Pareto-optimal design algorithm, requiring least computational work, is proposed for a single phase AC solenoid actuator with multi-design-objectives: maximizing holding force and minimizing eddy current loss simultaneously. In the algorithm, the design space is successively reduced by a suitable factor, as iteration repeats, with the center of pseudo-optimal point. At each iteration, the objective functions are approximated to a simple second-order response surface with the CCD sampling points generated within the reduced design space, and Pareto-optimal solutions are obtained by applying($1+{\lambda}$) evolution strategy with the fitness values of Pareto strength.

• Journal of the Chungcheong Mathematical Society
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• v.27 no.3
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• pp.523-530
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• 2014

In this article, we deal with the notion of ­${\Omega}$-limit sets in dynamical systems. We show that the ${\Omega}$­-limit set of a compact subset of a phase space is quasi-attracting.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.11-18
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• 2012

Debris flow deposition model is a model to predict affected areas by debris flow and random walk model (RWM) was used to build the model. Although the model was proved to be effective in the prediction of affected areas, the model has several free parameters decided experimentally. There are several well-known methods to estimate parameters, however, they cannot be applied directly to the debris flow problem due to the small size of training data. In this paper, a modified neural network, called pseudo sample neural network (PSNN), was proposed to overcome the sample size problem. In the training phase, PSNN uses pseudo samples, which are generated using the existing samples. The pseudo samples smooth the solution space and reduce the probability of falling into a local optimum. As a result, PSNN can estimate parameter more robustly than traditional neural networks do. All of these can be proved through the experiments using artificial and real data sets.