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differential evolution algorithms Comparison Used to Tune a Visual Control Law

IEEE ACCESS 2022年 10卷 46028-46042页

作者： Sanchez-Sanchez, Pablo Guillermo Cebada-Reyes, Jose Ruiz-Garcia, Agustin Montiel-Martinez, Aidee Reyes-Cortes, Fernando BUAP Fac Ciencias Elect Puebla 72530 Mexico Tecnol Nacl Mexico ITES Teziutlan Teziutlan 73960 Mexico UACH Dept Ingn Agr Texcoco 56230 Mexico

This paper presents the results of the comparative study of differential evolution algorithms used as an alternative for tuning the gains of a PD+ type visual control structure, since tuning PD or PID type control structures is not trivial. We made the quantitative comparison using the performance index (L-2-norm) and we applied the algorithm of best performance in a case of study (detection and cutting of leaves using a Cartesian robot). We also present the stability analysis according to Lyapunov theory and experimental results.

关键词： differential evolution algorithms PD plus type control structure performance index tuning control structures centroid visual-servoing plant tissue analysis leaves cutting

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Optimization of the LaBr3 detector model using differential evolution algorithms

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APPLIED RADIATION AND ISOTOPES 2025年 221卷 111841页

作者： Prozorova, Irina, V Sabitova, Radmila R. Bedenko, Sergey, V Irkimbekov, Ruslan A. Popov, Yuriy A. Svetachev, Stanislav N. Samarkhanov, Kuanysh K. Natl Nucl Ctr Republ Kazakhstan Inst Atom Energy Kurchatov 180010 Kazakhstan Natl Res Tomsk Polytech Univ Tomsk 634050 Russia

In gamma-ray spectrometry, computational detector model allows determining absolute detector efficiency for non-standard sources with varying chemical compositions in the absence of volumetric calibration standards. This study focuses on developing a computational model of a LaBr3(Ce) 1.5" x 1.5 '' scintillation detector based on characterization data. The detector was characterized using 137Cs and 152Eu point calibration sources placed at various positions relative to the detector cap. Modeling was performed using the MCNP6 code based on the Monte Carlo method. The initial modeling results revealed deviations between the calculated and experimental detector responses, which required model optimization. Optimization of the detector parameters was carried out using differential evolution algorithms. To verify the optimized LaBr3 model, studies were conducted with a volumetric KCl source. The deviations between the calculated and experimental results fell within the error limits.

关键词： Gamma-ray spectrometry Monte-carlo method Detector optimization Characterization differential evolution algorithms

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Visual Analysis of differential evolution algorithms 11th

Visual Analysis of Differential Evolution Algorithms

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11th International Conference on Multimedia and Network Information Systems (MISSI)

作者： Mexicano-Santoyo, A. Rodriguez-Jorge, R. Abrego, A. Jimenez, M. A. Zuniga-Trevino, R. Martinez-Garcia, Edgar A. Inst Tecnol Cd Victoria Mexico Univ Autonoma Ciudad Juarez Inst Engn & Technol Ciudad Juarez 32310 Chihuahua Mexico Univ Autonoma Tamaulipas Cd Victoria Mexico

ISBN: (纸本)9783319986784;9783319986777

In this article a web tool which contributes to the visual analysis of the differential evolution (DE) algorithms is presented. The tool provides a graphic interface with 8 views that allows understanding the underlying process of the algorithm. The tool has a library which extracts data from DE algorithms and its main feature is that the functions of the library can be embedded in the code of any DE algorithm to be analyzed. To validate the tool, three DE algorithms: DE/Rand/1/bin, DE/best/1/bin, and JADE and three test functions: Sphere, Rosenbrock, and Rastrigin have been used, which produced a total of 234 different tests, all of them performed successfully. The tool can allow to experts to analyze algorithms, particularly DE algorithms, and it can contribute to improve such algorithms or in generating new strategies that can emerge from the analysis of the extracted information.

关键词： differential evolution algorithms Algorithm analysis Web tool

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ROBUST CONTROL DESIGN TECHNIQUES USING differential evolution algorithms APPLIED TO THE PVTOL

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INTELLIGENT AUTOMATION AND SOFT COMPUTING 2014年第3期20卷 451-466页

作者： Lara, David Panduro, Marco Romero, Gerardo Alcorta, Efrain Betancourt, Romeo Autonomous Univ Tamaulipas Dept Elect Engn Cd Reynosa 88779 Tamaulipas Mexico Autonomous Univ Nuevo Leon FIME Monterrey Nl 66450 Mexico

In this paper, we present a strategy to stabilize the attitude of a planar vertical take off and landing (PVTOL) vehicle with variable pitch propeller (VPP) rotors. In the VPP configuration, the thrust is obtained with the propeller pitch angle, instead of changing the rotor speed, and this concept adds maneuverability to the vehicle. The PVTOL used in this paper is highly unstable in its natural hovering flight state, therefore the main goal is to achieve a stable attitude. First of all, a simplified dynamic model that includes the VPP dynamics is obtained. Then, a methodology to select the parameters of a nonlinear controller using differential evolution algorithms (DEA) will be presented. The controller's parameters are selected with two purposes: to guarantee the asymptotic stability of the closed-loop system while taking into account the uncertainty, and to improve its robustness margin. And finally, The results are validated with real-time experiments.

关键词： differential evolution algorithms PVTOL Robust control

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An embedded differential evolution approach to adaptive covariance inflation with the ensemble Kalman filter

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2024年第22期45卷 8425-8440页

作者： Bai, Yulong Yu, Qinghe Ma, Yongjie Northwest Normal Univ Coll Phys & Elect Engn 967 Anning East Rd Lanzhou Peoples R China

The limited ensemble sizes and the neglected model errors in ensemble-based Data Assimilation (DA) usually lead to underestimation of the error variance, and covariance inflation 'inflates' the covariance of a forecast or analysis ensemble by some positive factor in each assimilation cycle. In practice, the value of the inflation factor is often set by trial and error. Thus, a variety of adaptive covariance inflation (ACI) algorithms have been proposed to improve assimilation performance by adjusting the optimal parameters. Most of these used traditional optimization algorithms, such as gradient methods and relaxation methods. However, evolutionary algorithms(EAs), which encompass a range of population-based stochastic search techniques widely used in various engineering optimization problems, are rarely seen in DA. In this study, we developed a new framework for adaptive inflation factors, introducing differential evolution (DE) algorithm into local ensemble Transform Kalman filter (LETKF) that can explore the most suitable/optimal inflation factors online. A 'micro-DE' based data assimilation method can obtain better assimilation results step by step without taking a much longer time. The feasibility and effectiveness of the algorithm is demonstrated in an idealized Lorenz-96 model with simulated observations. Under both perfect and imperfect-model scenarios, it is found that the 'micro-DE'LETKF method is capable of outperforming the original LETKF with a considerable lower computational cost. The adaptive inflation factor is optimally updated at each assimilation cycle either around the upper bound or around the lower bound, which means that only an adaptive factor helps mitigate the ensemble collapse due to a lack of spread. However, the further study will consider the application of the methodology to more complex atmospheric models.

关键词： Ensemble Transform Kalman filter adaptive inflation differential evolution algorithms

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Ensemble of differential evolution algorithms for electromagnetic target recognition problem

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IET RADAR SONAR AND NAVIGATION 2013年第7期7卷 780-788页

作者： Secmen, Mustafa Tasgetiren, Mehmet Fatih Yasar Univ Dept Elect & Elect Engn Izmir Turkey Yasar Univ Dept Ind Engn Izmir Turkey

In this study, an ensemble of differential evolution (DE) algorithms is presented to classify electromagnetic targets in resonance scattering region. The algorithm aims to synthesize a special incident signal for each target, which is defined as the main discrimination feature in the given target recognition method. In the proposed algorithm, the amplitudes of basis functions and the duration of this incident signal are optimised to give minimum late-time scattered signal's energy, which is the main fitness function of the algorithm. The proposed DE algorithm is applied to a target set consisting of lossless dielectric spheres and correct recognition rates for both noiseless and noisy signals are obtained. The results for both developed DE algorithm and other DE variants of traditional DE, adaptive differential evolution with optional external archive (JADE), jDE are also given to compare the algorithms and show the effectiveness of the proposed one.

关键词： electromagnetic wave scattering object recognition signal detection jDE JADE noisy signals noiseless signals lossless dielectric spheres target set DE algorithm late-time scattered signal target recognition method discrimination feature resonance scattering region electromagnetic target classification electromagnetic target recognition problem differential evolution algorithms

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AMoDeBic: An adaptive Multi-objective differential evolution biclustering algorithm of microarray data using a biclustering binary mutation operator

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EXPERT SYSTEMS WITH APPLICATIONS 2024年第PartB期238卷

作者： Charfaoui, Younes Houari, Amina Boufera, Fatma Univ Mustapha STAMBOULI Mascara Mascara Algeria

In bioinformatics, biclustering is a crucial optimization task that can reveal hidden patterns and identify groups of genes that behave similarly under certain conditions. This study aims to efficiently identify high-quality and cohesive biclusters that share common characteristics across two data dimensions. To achieve this, we propose the first biclustering approach that utilizes Multi-objective differential evolution (DE), which is a novel technique for gene group discovery. Additionally, we introduce the Biclustering Binary differential evolution (BBDE), a new mutation operator that combines node addition and deletion, guided by an adaptive factor F. We thoroughly tested our method's effectiveness taking into account biological relevance, noise, overlap resistance, and statistics. We compared our results to state of the art algorithms using both synthetic and real datasets like Yeast Cell Cycle, Saccharomyces cerevisiae, and Human B Cell. Our algorithms outperformed the comparisons and effectively identified significant biclusters.

关键词： differential evolution algorithms Multi-objective differential evolution Biclustering evolutionary algorithms Micro-array data Knowledge discovery

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Furnace Temperature Curve Optimization Model Based on differential evolution Algorithm

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Journal of Electronic Research and Application 2024年第4期8卷 64-80页

作者： Yiming Cheng Merchant Marine College Shanghai Maritime UniversityShanghai 201308China

When soldering electronic components onto circuit boards,the temperature curves of the reflow ovens across different zones and the conveyor belt speed significantly influence the product *** study focuses on optimizing the furnace temperature curve under varying settings of reflow oven zone temperatures and conveyor belt *** address this,the research sequentially develops a heat transfer model for reflow soldering,an optimization model for reflow furnace conditions using the differential evolution algorithm,and an evaluation and decision model combining the differential evolution algorithm with the Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)*** approach aims to determine the optimal furnace temperature curve,zone temperatures of the reflow oven,and the conveyor belt speed.

关键词： Furnace temperature curve Difference equations differential evolution algorithms TOPSIS methods

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Multi-objective structural optimization for the automatic member grouping of truss structures using evolutionary algorithms

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COMPUTERS & STRUCTURES 2024年 292卷

作者： Carvalho, Jose Pedro G. Vargas, Denis E. C. Jacob, Breno P. Lima, Beatriz S. L. P. Hallak, Patricia H. Lemonge, Afonso C. C. Univ Fed Rio de Janeiro Civil Engn Program COPPE Rio De Janeiro Brazil Fed Ctr Technol Educ Minas Gerais Dept Math Belo Horizonte Brazil Univ Fed Juiz de Fora Sch Engn Dept Appl & Computat Mech Juiz De Fora Brazil

This paper aims to formulate the multi-objective structural optimization problem to find the best member group-ing of truss structures. The weight of the structure and the different number of discrete cross-sectional areas are the conflicting objective functions to be minimized simultaneously, generating a Pareto front presenting the non-dominated solutions. Sixteen multi-objective evolutionary algorithms are adopted to solve the proposed optimization problems. Several benchmark problems and a new proposed optimization problem are analyzed. Even though original groupings based on symmetry are defined, it is possible to discover other competitive structural member configurations that can interest decision-makers regarding manufacturing, cutting, transportation, checking, and welding.

关键词： Automatic member grouping Multi-objective structural optimization differential evolution algorithms Cardinality constraints

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A Novel Mathematical Modeling Approach to the Electric Dispatch Problem: case study using differential evolution algorithms

A Novel Mathematical Modeling Approach to the Electric Dispa...

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IEEE Congress on evolutionary Computation

作者： Marcelino, Carolina G. Wanner, Elizabeth F. Almeida, Paulo E. M. Ctr Fed Educ Tecnol Minas Gerais CEFET MG Intelligent Syst Lab LSI BR-30332025 Belo Horizonte MG Brazil

ISBN: (纸本)9781479904549;9781479904532

Nowadays, the population growth and economic development causes the need for electricity power to increase every year. An unit dispatch problem is defined as the attribution of operational values to each generation unit inside a power plant, given some criteria to be obeyed like the total power to be generated, operational bounds of these units etc. In this context, an optimal dispatch programming for hydroelectric units in energy plants provides a bigger production of electricity to be generated with a minimal water amount. This paper presents an optimization solution for hydroelectric generating system of a plant, using differential evolution algorithms. The novel mathematical model proposed and validation of the obtained algorithms will be performed with practical simulation experiments. Throughout the text, the equations and models for the system simulation will be fully described, and the experiments and results will be objectively analysed through statistical inference. Simulation results indicate savings of 6.5 million litres of water for each month of operation using the proposed solution.

关键词： Optimization differential evolution algorithms Simulation

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