Constrained Low-Cost Size Reduction of Wideband Antennas by Means of Enhanced Trust-Region Search Algorithm

2018 ◽  
Author(s):  
Adrian Bekasiewicz ◽  
Slawomir Koziel ◽  
Oinzsha S. Cheng ◽  
Song Li
Keyword(s):  
Search Algorithm ◽  
Low Cost ◽  
Trust Region ◽  
Size Reduction ◽  
Wideband Antennas ◽  
Region Search

scholarly journals Exact and Heuristic Methods for Observing Task-Oriented Satellite Cluster Agent Team Formation

2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Hao Chen ◽  
Shu Yang ◽  
Jun Li ◽  
Ning Jing
Keyword(s):  
Large Scale ◽  
Search Algorithm ◽  
Low Cost ◽  
Team Formation ◽  
Satellite Systems ◽  
Heuristic Search Algorithm ◽  
Earth Observation Satellite ◽  
Novel Algorithms ◽  
Swarm Intelligence Optimization ◽  
Task Oriented

With the development of aerospace science and technology, Earth Observation Satellite cluster which consists of heterogeneous satellites with many kinds of payloads appears gradually. Compared with the traditional satellite systems, satellite cluster has some particular characteristics, such as large-scale, heterogeneous satellite platforms, various payloads, and the capacity of performing all the observation tasks. How to select a subset from satellite cluster to perform all observation tasks effectively with low cost is a new challenge arousing in the field of aerospace resource scheduling. This is the agent team formation problem for observation task-oriented satellite cluster. A mathematical scheduling model is built. Three novel algorithms, i.e., complete search algorithm, heuristic search algorithm, and swarm intelligence optimization algorithm, are proposed to solve the problem in different scales. Finally, some experiments are conducted to validate the effectiveness and practicability of our algorithms.

scholarly journals Performance of the dynamically dimensioned search algorithm: influence of parameter initialization strategy when calibrating a physically based hydrological model

2017 ◽  
Vol 49 (4) ◽  
pp. 971-988 ◽  
Author(s):  
Franck Lespinas ◽  
Ashu Dastoor ◽  
Vincent Fortin
Keyword(s):  
Search Algorithm ◽  
Low Cost ◽  
Initial Parameter ◽  
Cost Strategy ◽  
Physically Based ◽  
Physically Based Models ◽  
Calibration Solution ◽  
Low Cost Strategy ◽  
Parameter Values ◽  
Initialization Strategy

Abstract This study presents an evaluation of the performance of the dynamically dimensioned search (DDS) algorithm when calibrating the hydrological component of the Visualizing Ecosystems for Land Management Assessments (VELMA) ecohydrological model. Two calibration strategies were tested for the initial parameter values: (1) a ‘high-cost strategy’, where 100 sets of initial parameter values were randomly chosen within the overall parameter space, and (2) a ‘low-cost strategy’, where a unique set of initial parameter values was derived from the available field data. Both strategies were tested for six different values of the maximum number of model evaluations ranging between 100 and 10,000. Results revealed that DDS is able to converge rapidly to a good parameter calibration solution of the VELMA hydrological component regardless of the parameter initialization strategy used. The accuracy and convergence efficiency of the DDS algorithm were, however, slightly better for the low-cost strategy. This study suggests that initializing the parameter values of complex physically based models using information on the watershed characteristics can increase the efficiency of the automatic calibration procedures.

scholarly journals Practical Implementation of an Indoor Robot Localization and Identification System using an Array of Anchor Nodes

2020 ◽  
Vol 16 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Israa AL-Forati ◽  
Abdulmuttalib Rashid
Keyword(s):  
Search Algorithm ◽  
Low Cost ◽  
Binary Search ◽  
Practical Implementation ◽  
Identification System ◽  
Robot Localization ◽  
Light Emitting ◽  
The Matrix ◽  
Anchor Nodes ◽  
Binary Search Algorithm

This paper proposes a low-cost Light Emitting Diodes (LED) system with a novel arrangement that allows an indoor multi-robot localization. The proposed system uses only a matrix of low-cost LED installed uniformly on the ground of an environment and low-cost Light Dependent Resistor (LDR), each equipped on bottom of the robot for detection. The matrix of LEDs which are driven by a modified binary search algorithm are used as active beacons. The robot localizes itself based on the signals it receives from a group of neighbor LEDs. The minimum bounded circle algorithm is used to draw a virtual circle from the information collected from the neighbor LEDs and the center of this circle represents the robot’s location. The propose system is practically implemented on an environment with (16*16) matrix of LEDs. The experimental results show good performance in the localization process.

Improved Trust Region Model Management for Approximate Optimization

1998 ◽  
Author(s):  
Brett A. Wujek ◽  
John E. Renaud
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Low Cost ◽  
Approximation Error ◽  
Trust Region ◽  
Model Management ◽  
Multidisciplinary Design ◽  
Test Problems ◽  
Approximation Techniques ◽  
Approximate Optimization

Abstract Approximations play an important role in multidisciplinary design optimization (MDO) by offering system behavior information at a relatively low cost. Most approximate optimization strategies are sequential in which an optimization of an approximate problem subject to design variable move limits is iteratively repeated until convergence. The move limits are imposed to restrict the optimization to regions of the design space in which the approximations provide meaningful information. In order to insure convergence of the sequence of approximate optimizations to a Karush Kuhn Tucker solution a move limit management strategy is required. In this paper, issues of move-limit management are reviewed and a new adaptive strategy for move limit management is developed. With its basis in the provably convergent trust region methodology, the TRAM (Trust region Ratio Approximation Method) strategy utilizes available gradient information and employs a backtracking process using various two-point approximation techniques to provide a flexible move-limit adjustment factor. The new strategy is successfully implemented in application to a suite of multidisciplinary design optimization test problems. These implementation studies highlight the ability of the TRAM strategy to control the amount of approximation error and efficiently manage the convergence to a Karush Kuhn Tucker solution.

Thermal morphing anisogrid smart space structures part 2: Ranking of geometric parameter importance, trust region optimization, and performance evaluation

2017 ◽  
Vol 24 (13) ◽  
pp. 2873-2893 ◽  
Author(s):  
Austin A Phoenix ◽  
Jeff Borggaard ◽  
Pablo A Tarazaga
Keyword(s):  
Parameter Optimization ◽  
Optimization Problem ◽  
Optimal Allocation ◽  
Search Algorithm ◽  
Thermal Strain ◽  
Computational Cost ◽  
Trust Region ◽  
Minimum Cost ◽  
Space Mission ◽  
Model Parameters

As future space mission structures are required to achieve more with scarcer resources, new structural configurations and modeling capabilities will be needed to meet the next generation space structural challenges. A paradigm shift is required away from the current structures that are static, heavy, and stiff, to innovative lightweight structures that meet requirements by intelligently adapting to the environment. As the complexity of these intelligent structures increases, the computational cost of the modeling and optimization efforts become increasingly demanding. Novel methods that identify and reduce the number of parameters to only those most critical considerably reduce these complex problems, allowing highly iterative evaluations and in-depth optimization efforts to be computationally feasible. This parameter ranking methodology will be demonstrated on the optimization of the thermal morphing anisogrid boom. The proposed novel morphing structure provides high precision morphing through the use of thermal strain as the sole actuation mechanism. The morphing concept uses the helical members in the anisogrid structure to provide complex constrained actuations that can achieve the six degree of freedom morphing capability. This structure provides a unique potential to develop an integrated structural morphing system, where the adaptive morphing capability is integrated directly into the primary structure. To identify parameters of interest, the Q-DEIM model reduction algorithm is implemented to rank the model parameters based on their impact on the morphing performance. This parameter ranking method provides insight into the system and enables the optimal allocation of computational and engineering resources to the most critical areas of the system for optimization. The methodology, in conjunction with a singular value decomposition (SVD), provides a ranking and identifies parameters of relative importance. The SVD is used to truncate the nine parameters problem at two locations, generating a five parameter optimization problem and a three parameter optimization problem. To evaluate the ranking, a parameter sweep in conjunction with a simple minimum cost function search algorithm will compare all 120 five parameter ranking orders to the Q-DEIM ranking. This reduced parameter set significantly reduces the parameter complexity and the computational cost of the model optimization. This paper will present the methodology to define the resulting performance of the optimal thermal morphing anisogrid structure, minimum morphing control, and the systems frequency response capability as a function of available power.

The License Plate Recognition Technology Based on Digital Image Processing

2011 ◽  
Vol 267 ◽  
pp. 778-782 ◽  
Author(s):  
Juan Hua Zhu ◽  
Ang Wu ◽  
Juan Fang Zhu
Keyword(s):  
Image Processing ◽  
Digital Image Processing ◽  
Digital Image ◽  
Convenient Method ◽  
Search Algorithm ◽  
Character Segmentation ◽  
Scale Transformation ◽  
License Plate ◽  
License Plate Recognition ◽  
Region Search

A rapid and convenient method of license plate recognition is discussed. The color plates are preprocessed by transform gray-scale transformation and image enhancement. The license plate is located by edge detection and region search algorithm, and the character segmentation is made by projection. Finally, the template is matched, and the license plate number is recognized quickly and accurately. The experiment shows that the method used in this paper can achieve better recognition results.

scholarly journals Design and Optimization of Compact Printed Log-Periodic Dipole Array Antennas with Extended Low-Frequency Response

Electronics ◽  
2021 ◽  
Vol 10 (17) ◽  
pp. 2044
Author(s):  
Keyur K. Mistry ◽  
Pavlos I. Lazaridis ◽  
Zaharias D. Zaharis ◽  
Tian Hong Loh
Keyword(s):  
Frequency Response ◽  
Low Frequency ◽  
Trust Region ◽  
Size Reduction ◽  
Antenna Design ◽  
Baseline Model ◽  
Design And Optimization ◽  
Novel Technique ◽  
Array Antennas ◽  
Lower Frequencies

This paper initially presents an overview of different miniaturization techniques used for size reduction of printed log-periodic dipole array (PLPDA) antennas, and then continues by presenting a design of a conventional PLPDA design that operates from 0.7–8 GHz and achieves a realized gain of around 5.5 dBi in most of its bandwidth. This antenna design is then used as a baseline model to implement a novel technique to extend the low-frequency response. This is completed by replacing the longest straight dipole with a triangular-shaped dipole and by optimizing the four longest dipoles of the antenna using the Trust Region Framework algorithm in CST. The improved antenna with extended low-frequency response operates from 0.4 GHz to 8 GHz with a slightly reduced gain at the lower frequencies.

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