检索结果-内蒙古大学图书馆

A new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-iii for powertrain mount system

引用

JOURNAL OF VIBRATION AND CONTROL 2020年第13-14期26卷 1187-1198页

作者： Guo, Li-Xin Dinh-Nam Dao Northeastern Univ Sch Mech Engn & Automat 3-11 Wenhua Rd Shenyang 110819 Peoples R China Le Quy Don Tech Univ Control Technol Coll Hanoi Vietnam

This article presents a new control method based on fuzzy controller, time delay estimation, deep learning, and non-dominated sorting genetic algorithm-iii for the nonlinear active mount systems. The proposed method, intelligent adapter fractions proportional-integral-derivative controller, is a smart combination of the time delay estimation control and intelligent fractions proportional-integral-derivative with adaptive control parameters following the speed range of engine rotation via the deep neural network with the optimal non-dominated sorting genetic algorithm-iii deep learning algorithm. Besides, we proposed optimal fuzzy logic controller with optimal parameters via particle swarm optimization algorithm to control reciprocal compensation to eliminate errors for intelligent adapter fractions proportional-integral-derivative controller. The control objective is to deal with the classical conflict between minimizing engine vibration impacts on the chassis to increase the ride comfort and keeping the dynamic wheel load small to ensure the ride safety. The results of this control method are compared with that of traditional proportional-integral-derivative controller systems, optimal proportional-integral-derivative controller parameter adjustment using genetic algorithms, linear-quadratic regulator control algorithms, and passive drive system mounts. The results are tested in both time and frequency domains to verify the success of the proposed optimal fuzzy logic controller-intelligent adapter fractions proportional-integral-derivative control system. The results show that the proposed optimal fuzzy logic controller-intelligent adapter fractions proportional-integral-derivative control system of the active engine mount system gives very good results in comfort and softness when riding compared with other controllers.

关键词： Active mount system fuzzy control deep learning non-dominated sorting genetic algorithm-iii time delay estimation fractions proportional-integral-derivative controller

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization of gradient gas diffusion layer structures for enhancing proton exchange membrane fuel cell performance based on response surface methodology and non-dominated sorting genetic algorithm-iii

引用

ENERGY 2024年 288卷

作者： Chen, Ke Luo, Zongkai Zou, Guofu He, Dandi Xiong, Zhongzhuang Zhou, Yu Chen, Ben Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan 430070 Peoples R China Hubei Collaborat Innovat Ctr Automot Components Te Wuhan 430070 Peoples R China

The gas diffusion layer structure has a significant impact on water and gas transport in proton exchange membrane fuel cell (PEMFC). In this study, a multi-objective optimization (MOO) method is applied to optimize the PEMFC gas diffusion layer (GDL) structures for performance enhancement. Nine design parameters are studied to analyses the output performance of the fuel cell and the average water content of the membrane, oxygen concentration non-uniformity, power density and system efficiency are used as performance indexes. The MOO forms the response surface regression model based on the three-dimensional numerical model of PEMFC, and the response surface methodology after processing through the non-dominated sorting genetic algorithm-iii (NSGA-iii) to obtain the Pareto frontier, and prioritizes the best operating conditions and structures based on technique for order preference by similarity to an ideal solution (TOPSIS). Compared with the reference point, the performance indexes of the decision point obtained by the NSGA-iii algorithm and TOPSIS algorithm is enhanced by 0.45 %, 42.06 %, 2.99 % and 0.25 %, respectively. This study presents a new multi-objective optimization method for optimizing operating conditions combine with GDL structures for building efficient PEMFC, which provides a solution for achieving higher performance. The optimal results in this paper can provide some guidance for fuel cell performance improvement and control optimization.

关键词： PEMFC Gradient gas diffusion layer Operating conditions Multi-objective optimization Response surface methodology non-dominated sorting genetic algorithm-iii

来源：评论

学校读者我要写书评

暂无评论

Intelligent optimization: Novel application of PCC, MCDM, and ANN plus NSGA-iii in integrated optimization of the flow field and porous layer structures for unitized regenerative fuel cell

引用

APPLIED ENERGY 2024年 374卷

作者： Chen, Ke Chen, Wenshang Zou, Guofu Chen, Ben Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan 430070 Peoples R China Hubei Collaborat Innovat Ctr Automot Components Te Wuhan 430070 Peoples R China

Unitized Regenerative Fuel Cells (URFCs) are a promising technology that utilizes renewable energy sources to efficiently convert them into electricity while offering potential for renewable energy storage. These cells facilitate the conversion between electrical and chemical energy, enabling processes such as electrolysis and hydrogen gas synthesis from water. This study aims to propose a more efficient and stable mass transfer solution for URFCs through the integrated optimization of flow field structure and porous transport layer configuration. Leveraging Taguchi orthogonal design, Pearson correlation coefficient, contour analysis, multi-criteria decision making, and the integration of artificial neural networks with non-dominated sorting genetic algorithm-iii, an optimized selection is performed. Results indicate that the optimized structure exhibits improved performance in both electrolytic cell (EC) and fuel cell (FC) modes. At a current density of 1.5 A/cm2, compared to traditional structures, the voltage decreases by 8.2 mV in the EC mode. In the FC mode at a current density of 1.0 A/cm2, performance improves by 5.748%, and URFC round-trip efficiency increases by 6.183%. The assessment of mass transfer capability reveals that the optimized structure promotes gas transfer processes in different modes, leading to significant overall performance enhancement of URFC. These findings provide valuable guidance for the enhanced performance of URFC.

关键词： URFCs Integrated optimization Pearson correlation coefficient Multi-criteria decision making Artificial neural networks non-dominated sorting genetic algorithm-iii

来源：评论

学校读者我要写书评

暂无评论

Many-objective approach based on problem-aware mutation operators for protein encoding

引用

INFORMATION SCIENCES 2022年 613卷 376-400页

作者： Diaz-Galian, Maria Victoria Vega-Rodriguez, Miguel A. Univ Extremadura Escuela Politecn Campus Univ S-N Caceres 10003 Spain

One of the research pathways in synthetic biology is protein encoding, which aims to improve and increase protein expression. The production of heterologous proteins is important in different fields, such as medicine, environmental biology, and agriculture. Protein encoding is a difficult task and can be defined as a many-objective optimization problem, where four objectives must be optimized concurrently: codon adaptation, guanine-cytosine content, difference between sequences, and avoidance of hairpin loops. These objectives are why we propose and describe a many-objective approach based on the non-dominated sorting genetic algorithm-iii (NSGA-iii) for protein encoding. The proposed algorithm was designed to work with novel mutation operators that are problem-aware and consider the different optimization objectives. The results of the pro-posed algorithm were compared to those of different tools that were reported by other authors to determine its efficiency. Comparisons were made using several quality metrics and with statistical analyses. The average improvements in hypervolume and set coverage were between 5.34% and 55.75%, and 53.01% and 100%, respectively. Based on the statisti-cal analyses, the proposed algorithm was found to produce statistically significant improvements compared to other algorithms, thus highlighting the relevance of the proposed approach for protein encoding.(c) 2022 Elsevier Inc. All rights reserved.

关键词： Many-objective optimization problem non-dominated sorting genetic algorithm-iii Problem-aware mutations Bioinformatics Protein encoding

来源：评论

学校读者我要写书评

暂无评论

Evolution of the microstructure and multi-objective optimization of the tensile properties of GH3625 superalloy by selective laser melting

引用

JOURNAL OF MATERIALS RESEARCH AND TECHNOLOGY-JMR&T 2023年 24卷 8826-8848页

作者： Zeng, Quan Wang, Kelu Lu, Shiqiang Lu, Cuiyuan Wang, Zengqiang Zhou, Tong Nanchang Hangkong Univ Sch Aeronaut Mfg Engn Nanchang 330063 Peoples R China Nanchang Univ Sch Adv Mfg Nanchang 330063 Peoples R China

Selective laser melting (SLM) is one of the most widely used metal additive manufacturing (AM) technologies and has great potential for forming complex structured parts. As GH3625 super -alloy becomes more demanding for complex structured parts, making SLM offers a unique opportunity for manufacturing complex structured superalloys. However, there are relatively few studies on the microstructural evolution of GH3625 superalloys prepared by SLM, and the high tensile strength but the low elongation of superalloy parts prepared by SLM are difficult to meet practical applications. To this end, the effects of different volume energy densities (VEDs) on the microstructure and fracture characteristics of superalloys are investigated in this paper. In addition, a method combining response surface methodology (RSM) with non-dominated ranking genetic algorithm-iii (NSGA-iii) is proposed to generate optimal process parameters to maximize yield strength, ultimate tensile strength and elongation of superalloys. To demonstrate that the application of the NSGA-iii algorithm is outstanding, the NSGA-II algo-rithm is considered for application to this optimization problem and the hypervolume (HV) index is used to objectively evaluate the superiority of these algorithms. The best Pareto front obtained is also verified. The results show that the melt pool size is proportional to the VED in the studied range, and the deepest molten pool is about 74 mm when the VED is 147.62 J/mm3;the smallest cellular grain in the XOY direction is about 0.27 mm when the VED is 66.14 J/mm3. In the optimization of tensile properties, the yield strength, ultimate tensile strength and elongation models constructed by RSM are significant with R2 of 0.991, 0.9621 and 0.9391, in that order. The evaluation index HV indicates that the Pareto front obtained by NSGA-iii has a higher priority than the Pareto Front obtained by NSGA-II with HV Finally, the obtained Pareto front was experimentally verified and the ma

关键词： Selective laser melting Multi-objective optimization Response surface methodology non-dominated sorting genetic algorithm-iii Microstructure evolution

来源：评论

学校读者我要写书评

暂无评论

Uplink Data Transmission Based on Collaborative Beamforming in UAV-assisted MWSNs

Uplink Data Transmission Based on Collaborative Beamforming ...

引用

IEEE Global Communications Conference (GLOBECOM)

作者： Wang, Aimin Wang, Yuxin Sun, Geng Li, Jiahui Liang, Shuang Liu, Yanheng Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Sch Math Changchun 130012 Peoples R China

ISBN: (纸本)9781728181042

Unmanned aerial vehicles (UAVs) have attracted growing attention in enhancing the performance of mobile wireless sensor networks (MWSNs) since they can act as the aerial base stations (ABSs) and have the autonomous nature to collect data. In this paper, we consider to construct a virtual antenna array (VAA) consists of mobile sensor nodes (MSNs) and adopt the collaborative beamforming (CB) to achieve the long-distance and efficient uplink data transmissions with the ABSs. First, we formulate a high data transmission rate multi-objective optimization problem (HDTRMOP) of the CB-based UAV-assisted MWSN to simultaneously improve the total transmission rates, suppress the total maximum sidelobe levels (SLLs) and reduce the total motion energy consumptions of MSNs by jointly optimizing the positions and excitation current weights of MSN-enabled VAA, and the order of communicating with different ABSs. Then, we propose an improved non-dominated sorting genetic algorithm-iii (INSGA-iii) with chaos initialization, average grade mechanism and hybrid-solution generate strategy to solve the problem. Simulation results verify that the proposed algorithm can effectively solve the formulated HDTRMOP and it has better performance than some other benchmark methods.

关键词： Mobile wireless sensor networks unmanned aerial vehicles collaborative beamforming non-dominated sorting genetic algorithm-iii multi-objective optimization problem

来源：评论

学校读者我要写书评

暂无评论

Multi-objective uplink data transmission optimization for edge computing in UAV-assistant mobile wireless sensor networks

引用

JOURNAL OF SYSTEMS ARCHITECTURE 2022年 132卷

作者： Li, Jiahui Sun, Geng Liang, Shuang Wang, Yuxin Wang, Aimin Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Key Lab Symbol Computat Knowledge Engn Minist Educ Changchun 130012 Peoples R China

Unmanned aerial vehicles (UAVs) have attracted growing attention in enhancing the performance of mobile wireless sensor networks (MWSNs) since they can act as aerial servers (ASs) and have the autonomous nature to collect data for edge computing. In this paper, we consider to construct a virtual antenna array (VAA) consists of mobile sensor nodes (MSNs) and adopt collaborative beamforming (CB) to achieve long-distance and efficient uplink data transmissions with the ASs. First, we formulate a low interference and high-performance uplink transmission multi-objective optimization problem (UTMOP) of the CB-based UAV-assisted MWSN to simultaneously improve the total transmission rates, suppress the total maximum sidelobe levels (SLLs) and reduce the total propulsion energy consumptions of MSNs by jointly optimizing the positions and excitation current weights of MSN-enabled VAA and the order of communicating with different ASs. Then, we propose an improved non-dominated sorting genetic algorithm-iii (INSGA-iii) with chaos initialization, average grade mechanism and hybrid-solution generate strategy to solve the problem. Simulation results verify that the proposed algorithm can effectively solve the formulated UTMOP, and it has better performance than some other benchmark methods and peer algorithms.

关键词： Mobile wireless sensor networks Unmanned aerial vehicles Collaborative beamforming non-dominated sorting genetic algorithm-iii Multi-objective optimization problem

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：