scholarly journals Evolutionary Optimization of Multirendezvous Impulsive Trajectories

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Lorenzo Federici ◽  
Alessandro Zavoli ◽  
Guido Colasurdo
Keyword(s):  
Time Window ◽  
Differential Evolution Algorithm ◽  
Orbital Plane ◽  
Combinatorial Problem ◽  
Simultaneous Optimization ◽  
Artificial Satellites ◽  
Problem Solution ◽  
Suggested Approach ◽  
Level Problem ◽  
The Time Domain

This paper investigates the use of evolutionary algorithms for the optimization of time-constrained impulsive multirendezvous missions. The aim is to find the minimum- Δ V trajectory that allows a chaser spacecraft to perform, in a prescribed mission time, a complete tour of a set of targets, such as space debris or artificial satellites, which move on the same orbital plane at slightly different altitudes. For this purpose, a two-level design approach is pursued. First, an outer-level combinatorial problem is defined, dealing with the simultaneous optimization of the sequence of targets and the rendezvous epochs. The suggested approach is first tested by assuming that all transfer legs last exactly the same amount of time; then, the time domain is discretized over a finer grid, allowing a more appropriate sizing of the time window allocated for each leg. The outer-level problem is solved by an in-house genetic algorithm, which features an effective permutation-preserving solution encoding. A simple, but fairly accurate, heuristic, based on a suboptimal four-impulse analytic solution of the single-target rendezvous problem, is used when solving the combinatorial problem for a fast guess at the transfer cost, given the departure and arrival epochs. The outer-level problem solution is used to define an inner-level NLP problem, concerning the optimization of each body-to-body transfer leg. In this phase, the encounter times are further refined. The inner-level problem is tackled through an in-house multipopulation self-adaptive differential evolution algorithm. Numerical results for case studies including up to 20 targets with different time grids are presented.

Algoritma Fisher-Yates Shuffle dan Flood Fill sebagai Maze Generator pada Game Labirin

2019 ◽  
Vol 10 (2) ◽  
pp. 59-64
Author(s):  
D.J. Owen Hoetama ◽  
Farica Perdana Putri ◽  
P.M. Winarno
Keyword(s):  
Hamming Distance ◽  
Problem Solution ◽  
Average Percentage ◽  
Rate Difference ◽  
Level Problem ◽  
Index Terms ◽  
Flood Fill ◽  
Static Level ◽  
Wall Position

Maze game is an interesting game and used to spend time. However, in the maze game, the level used forthis game still uses static levels. Static levels make the maze shape stay the same if we play the same level. Thus, players will quickly feel bored because it finds the same complexity. Maze generator is a static level problem solution on the maze game. This research uses Fisher-Yates Shuffle algorithm and Flood Fill algorithm to make maze generator. Fisher-Yates Shuffle algorithm is used for wall position randomization and Flood Fill algorithm to keep the maze results to remain resolved. The results of the application implementation yielded 30 mazes and were tested using the Hamming Distance algorithm, yielding that the result of the maze formed is always different. The average percentage rate difference produced 48% each time the maze was formed. The results of the maze that was formed performed perfect maze checking with the result of 83.33% percentage. Index Terms— Fisher-Yates Shuffle, Flood Fill, MazeGenerator, Hamming Distance

Neuronal Synchronization and Selective Color Processing in the Human Brain

2004 ◽  
Vol 16 (3) ◽  
pp. 503-522 ◽  
Author(s):  
Matthias M. Müller ◽  
Andreas Keil
Keyword(s):  
Large Scale ◽  
Time Course ◽  
Time Window ◽  
Brain Activity ◽  
Stimulus Onset ◽  
Gamma Band ◽  
Event Related Potential ◽  
Alpha Band ◽  
Color Processing ◽  
The Time Domain

In the present study, subjects selectively attended to the color of checkerboards in a feature-based attention paradigm. Induced gamma band responses (GBRs), the induced alpha band, and the event-related potential (ERP) were analyzed to uncover neuronal dynamics during selective feature processing. Replicating previous ERP findings, the selection negativity (SN) with a latency of about 160 msec was extracted. Furthermore, and similarly to previous EEG studies, a gamma band peak in a time window between 290 and 380 msec was found. This peak had its major energy in the 55to 70-Hz range and was significantly larger for the attended color. Contrary to previous human induced gamma band studies, a much earlier 40to 50-Hz peak in a time window between 160 and 220 msec after stimulus onset and, thus, concurrently to the SN was prominent with significantly more energy for attended as opposed to unattended color. The induced alpha band (9.8–11.7 Hz), on the other hand, exhibited a marked suppression for attended color in a time window between 450 and 600 msec after stimulus onset. A comparison of the time course of the 40to 50-Hz and 55to 70-Hz induced GBR, the induced alpha band, and the ERP revealed temporal coincidences for changes in the morphology of these brain responses. Despite these similarities in the time domain, the cortical source configuration was found to discriminate between induced GBRs and the SN. Our results suggest that large-scale synchronous high-frequency brain activity as measured in the human GBR play a specific role in attentive processing of stimulus features.

scholarly journals A Nonlinear Adaptive Observer-Based Differential Evolution Algorithm to Multiparameter Fault Diagnosis

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xiaoliu Yang ◽  
Zetao Li ◽  
Qingfang Zhang ◽  
Qinmu Wu ◽  
Linli Yang
Keyword(s):  
Differential Evolution ◽  
Fitness Function ◽  
Differential Evolution Algorithm ◽  
Adaptive Observer ◽  
Identification System ◽  
Water Tank ◽  
Suggested Approach ◽  
Differential Evolutionary Algorithm ◽  
On Line ◽  
Evolution Algorithm

In this paper, a novel adaptive diagnosis scheme is proposed for multiparametric faults of nonlinear systems by using the model and intelligent optimization-based approaches. The key idea of the proposed method is to analyze the correlation of the output signals between the real system and the fault identification system instead of residual. A new adaptive scheme is built based on an adaptive observer and differential evolution algorithm. Meanwhile, the conditions of detectability and identifiability of faults are analyzed. The isolation and estimation of the multiparametric fault are formulated as the solution of an optimization problem that is solved by using a differential evolutionary algorithm (DE). The fitness function of DE is constructed by the correlation coefficient equations in which the faulty components are contained. The application on a coupled three water tank model attests the feasibility and validity of the suggested approach. Simulation and experimental results show that the developed method is applicable to diagnose either single or multiparameter faults on-line.

scholarly journals Calculation of Stress Intensity Factor for an Internal Circumferential Crack in a Rotating Functionally Graded Thick-Walled Hollow Circular Cylinder under Thermal Shock

2017 ◽  
Vol 64 (4) ◽  
pp. 455-479 ◽  
Author(s):  
Mohammad Reza Ghafoor Elahi ◽  
Masoud Mahdizadeh Rokhi
Keyword(s):  
Stress Intensity ◽  
Functionally Graded ◽  
Problem Solution ◽  
Mechanical Shock ◽  
Axially Symmetric ◽  
Extended Finite Element ◽  
Dynamic Stress Intensity Factors ◽  
Graded Materials ◽  
Circumferential Crack ◽  
The Time Domain

Abstract In this article, the fracture behavior of functionally graded thick-walled cylinder under thermo-mechanical shock is investigated. For this purpose, classical coupled thermoelastic equations are used in calculations. First, these equations are discretized with extended finite element method (XFEM) in the space domain and then they are solved by the Newmark method in the time domain. The most general form of interaction integral is extracted for axially symmetric circumferential crack in a cylinder under thermal and mechanical loads in functionally graded materials and is used to calculate dynamic stress intensity factors (SIFs). The problem solution has been implemented in MATLAB software.

scholarly journals Hamiltonian path problem solution using DNA computing

2020 ◽  
pp. 69-74
Author(s):  
Anna Sergeenko ◽  
Maria Yakunina ◽  
Oleg Granichin
Keyword(s):  
Branch And Bound ◽  
Dna Computing ◽  
Hamiltonian Path ◽  
Combinatorial Problem ◽  
Problem Solution ◽  
Branch And Bound Method ◽  
Popular Method ◽  
Time Consumption ◽  
Hamiltonian Path Problem ◽  
Classical Algorithm

In this article we study DNA computing, a method which is based on working with DNA molecules in a laboratory. That approach is implemented in solving one of the most popular combinatorial problem — the Hamiltonian path problem. Related to recent improvements in the biophysics methods, which are needed for DNA computing, we propose to change some steps in the classical algorithm to increase accuracy of this method. The branch-and-bound method, the most popular method which is realized on a computer, is also shown in this paper to compare its performance with the time consumption of DNA computing. The results of that comparison prove that it becomes inefficient to use the branch-and-bound method from the counted number of vertices because of its exponentially growing complexity, while DNA computing works parallel and has linearly growing time consumption.

scholarly journals Modal Analysis Problem Solution for a Mathematical Model Formed by the Extended Nodal Method

2021 ◽  
pp. 33
Author(s):  
V. A. Trudonoshin ◽  
V. A. Ovchinnikov ◽  
V. G. Fedoruk
Keyword(s):  
Mathematical Model ◽  
Normal Form ◽  
Modal Analysis ◽  
Jacobi Matrix ◽  
Problem Solution ◽  
State Variables ◽  
Equilibrium Equations ◽  
Algebraic Form ◽  
Nodal Method ◽  
The Time Domain

The article proposes an option for transforming a mathematical model of the object, formed by the extended nodal method in the time-domain solution for modal analysis. Since finding the eigenvalues ​​and eigenvectors for systems of ordinary equations given in the Cauchy normal form is possible, calculations are presented that allow us to obtain a system of equations in the Cauchy normal form from a mathematical model in a differential-algebraic form through linearization. The extended nodal method contains derivatives of state variables in the vector of unknown, and the Jacobi matrix obtained at each Newton iteration of each step of numerical integration can be used to obtain a linearized mathematical model, but the equilibrium equations, as a rule, contain several derivatives with respect to time. By introducing additional variables, it is possible to reduce the linearized mathematical model to the Cauchy normal form, while the Jacobi matrix structure remains essentially unchanged.The proposed solution is implemented in the mathematical core of the PRADIS Gen2 PA-8 software package, which made it possible to expand its functionality by an operator of modal analysis.The presented calculations of test schemes have shown the correctness of the method proposed.

scholarly journals Parameter and State Estimation for Uncertain Nonlinear Systems by Adaptive Observer Based on Differential Evolution Algorithm

2020 ◽  
Vol 10 (17) ◽  
pp. 5857
Author(s):  
Xiaoliu Yang ◽  
Zetao Li ◽  
Boutaib Dahhou
Keyword(s):  
Differential Evolution ◽  
Time Window ◽  
Differential Evolution Algorithm ◽  
Time Estimation ◽  
Joint Estimation ◽  
Adaptive Observer ◽  
Global Optimality ◽  
System Nonlinearity ◽  
Real Time Estimation ◽  
Evolution Algorithm

This paper puts forward a new adaptive observer scheme for joint estimation of state and multi-parameters for nonlinear dynamic systems. The adaptive observer uses chaos differential evolution algorithm to improve global optimality of estimation in the case of multi-parameter and system nonlinearity. Slide time window is used to realize real-time estimation. The simulation result shows the effectiveness of the adaptive observer.

scholarly journals Synthesis of Linear Array Antenna for Required Range of Beam Width Using Optimization Algorithms

2018 ◽  
Vol 7 (3.31) ◽  
pp. 16
Author(s):  
N Venkateswara rao ◽  
G Challa Ram
Keyword(s):  
Linear Array ◽  
Optimization Algorithms ◽  
Differential Evolution Algorithm ◽  
Beam Width ◽  
Side Lobe ◽  
Array Antenna ◽  
Simultaneous Optimization ◽  
Side Lobe Level ◽  
Wide Range ◽  
Evolution Algorithm

In an application like radar there is a need for a wide range of Beam widths depending on whether the radar is operating in search mode or tracking mode. Wide range of beam widths can be achieved by using optimization algorithms like Biogeography-based optimization (BBO) and Differential Evolution Algorithm (DE). The desired beam width should be achieved without any significant increase in the side lobe level (SLL). This can be done by optimizing both SLL and FNBW simultaneously. Synthesis of linear array antenna for a fixed range of beam width is obtained by using the proposed methodology. The results for simultaneous optimization of FNBW and SLL using BBO and DE algorithms are compared.  

Temporal windowing and inverse transform of the wavefield in the Laplace-Fourier domain

Geophysics ◽  
2013 ◽  
Vol 78 (5) ◽  
pp. R207-R222 ◽  
Author(s):  
Sangmin Kwak ◽  
Hyunggu Jun ◽  
Wansoo Ha ◽  
Changsoo Shin
Keyword(s):  
Fourier Transform ◽  
Time Window ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Fourier Domain ◽  
Gain Function ◽  
The Fourier Transform ◽  
The Time Domain ◽  
Derivatives Of ◽  
Complex Damping

Temporal windowing is a valuable process, which can help us to focus on a specific event in a seismogram. However, applying the time window is difficult outside the time domain. We suggest a windowing method which is applicable in the Laplace-Fourier domain. The window function we adopt is defined as a product of a gain function and an exponential damping function. The Fourier transform of a seismogram windowed by this function is equivalent to the partial derivative of the Laplace-Fourier domain wavefield with respect to the complex damping constant. Therefore, we can obtain a windowed seismogram using the partial derivatives of the Laplace-Fourier domain wavefield. We exploit the time-windowed wavefield, which is modeled directly in the Laplace-Fourier domain, to reconstruct subsurface velocity model by waveform inversion in the Laplace-Fourier domain. We present the windowed seismograms by introducing an inverse Laplace-Fourier transform technique and demonstrate the effect of temporal windowing in a synthetic Laplace-Fourier domain waveform inversion example.

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