检索结果-内蒙古大学图书馆

differential evolution algorithm based Double Integral Sliding Mode Control for Maximum Power Point Tracking of a standalone photovoltaic system

引用

RENEWABLE ENERGY 2025年 244卷

作者： Rizki, H. Boufounas, E. -m. El Amrani, A. El Amraoui, M. Bejjit, L. Moulay Ismail Univ Meknes Higher Sch Technol Meknes LASMAR Lab MIN Res Grp Meknes Morocco Moulay Ismail Univ Meknes Fac Sci & Technol REIPT Lab BP 509 Boutalamine Errachidia Morocco Moulay Ismail Univ Meknes Fac Sci Meknes LASMAR Lab Meknes Morocco

The purpose of this study is to develop a robust control strategy based on the Sliding Mode Control (SMC) method and its advanced form of Double Integral Sliding Mode Control (DISMC) enhanced by a differential evolution (DE) algorithm. This approach focuses on offering a strong and effective method to adjust the controller parameters to minimize the tracking error between the PV output voltage and the reference. The DE algorithm uses initialization, mutation, crossover, and selection phases to accurately find the optimal controller coefficients for effectively implementing the control strategy of DISMC. The present paper highlights the superior performance of DE-DISMC compared to other controllers optimized with conventional methods, demonstrating its ability to provide the highest stability, accuracy, and efficiency to optimize the Maximum Power Point Tracking (MPPT) process. Using real climatic data from Errachidia city which is located in the south-east of Morocco, this work illustrates DE-DISMC's ability to maintain the PV system's peak performance in the face of varying environmental conditions, and the Lyapunov analysis confirms the system's stability. The results of this study are evaluated using various statistical and analytical metrics, including response time, magnitude of chattering, steady-state error, and efficiency. The findings highlight the high performance of the proposed DE-DISMC controller, especially under real climatic test conditions, achieving a response time of 1.1 ms, which is 58% faster than DE-ISMC and 89% than DE-CSMC, along with a negligible chattering magnitude of 2.8 x 10-6 V. It also demonstrates strong resilience and effectiveness, reaching a minimal steady-state error of 0.00014 V and a high efficiency of 99.99%. This balance makes DE-DISMC a reliable control solution, especially in changing environmental conditions.

关键词： Photovoltaic systems Maximum Power Point Tracking Sliding Mode Control Double Integral Sliding Mode Control Intelligent control differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

differential evolution algorithm with dynamic multi-population applied to flexible job shop schedule

引用

ENGINEERING OPTIMIZATION 2022年第3期54卷 387-408页

作者： Cao, Yang Shi, Haibo Chang, DaLiang Northeastern Univ Coll Informat Sci & Engn Shenyang Peoples R China Chinese Acad Sci Shenyang Inst Automat Shenyang Peoples R China Chinese Acad Sci Inst Robot Shenyang Peoples R China Chinese Acad Sci Inst Intelligent Mfg Shenyang Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Key Lab Network Control Syst Shenyang Peoples R China Shenyang Jianzhu Univ Informat & Control Engn Fac Shenyang Peoples R China

This article proposes a novel differential evolution algorithm based on dynamic multi-population (DEDMP) for solving the multi-objective flexible job shop scheduling problem. In DEDMP, at each generation, the whole population is divided into several subpopulations by the clustering partition and the size of the subpopulation is dynamically adjusted based on the last search experience. Furthermore, DEDMP is adaptive based on two search strategies, one with strong exploration ability and the other with strong exploitation ability. The selection probability of each search strategy is also dynamically adjusted according to the success rate. Furthermore, the proposed algorithm adopts newly designed mutation and crossover operators and it can directly generate feasible solutions in the search space. To evaluate the performance of DEDMP, DEDMP is compared with some state-of-the-art algorithms on benchmark instances. The experimental results show that DEDMP is better than or at least competitive with other outstanding algorithms.

关键词： Flexible job shop scheduling problem differential evolution algorithm multi-objective optimization multiple subpopulations strategy adaptation

来源：评论

学校读者我要写书评

暂无评论

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the differential evolution algorithm

引用

IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1836-1848页

作者： Wei Qian Yanmin Wu Bo Shen School of Electrical Engineering and Automation Henan Polytechnic UniversityJiaozuo 454000China College of Information Science and Technology Donghua UniversityShanghai 201620China

This article mainly investigates the fuzzy optimization robust control issue for nonlinear networked systems characterized by the interval type-2(IT2)fuzzy technique under a differential evolution *** provide a more reasonable utilization of the constrained communication channel,a novel adaptive memory event-triggered(AMET)mechanism is developed,where two event-triggered thresholds can be dynamically adjusted in the light of the current system information and the transmitted historical *** conditions with less conservative design of the fuzzy imperfect premise matching(IPM)controller are presented by introducing the Wirtinger-based integral inequality,the information of membership functions(MFs)and slack ***,under the IPM policy,a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 TakagiSugeno(T-S)fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control ***,simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.

关键词： Adaptive memory event-triggered(AMET) differential evolution algorithm fuzzy optimization robust control interval type-2(IT2)fuzzy technique.

来源：评论

学校读者我要写书评

暂无评论

Real-time torque prediction for ultrasonic motors using an attention-based BiLSTM model and improved differential evolution algorithm

引用

MEASUREMENT 2025年 251卷

作者： Wang, Yanbo Sasamura, Tatsuki Mustafa, Abdullah Morita, Takeshi Univ Tokyo Dept Precis Engn Hongo 7-3-1Bunkyo Ku Tokyo 1138656 Japan Univ Tokyo Dept Human & Engn Environm Studies Kashiwa No Ha 5-1-5 Kashiwa 2778563 Japan

Ultrasonic motors (USMs), characterized by their miniaturization, high precision, and low noise, are widely utilized in robotics, medical devices, and aerospace applications. However, existing torque control methods are heavily dependent on sensors, which not only increase system cost and complexity but also restrict the deployment of USMs in space-constrained environments, thereby undermining their miniaturization advantages. Furthermore, the complex nonlinear torque characteristics and significant temperature effects of USMs have made traditional torque prediction methods based on physical models inadequate to meet the high-precision requirements of practical applications. To address these challenges, a real-time torque prediction method based on a hybrid attention mechanism, Hodrick-Prescott (HP) decomposition, and bidirectional long short-term memory (BiLSTM) network is proposed in this study. HP decomposition is employed to effectively capture both long-term trends and short-term fluctuations in time series data. The hybrid attention mechanism further highlights key input variables by distributing weights across time steps and feature dimensions. Finally, an improved differential evolution algorithm is applied to optimize the attention weights, enhancing model performance and reducing manual tuning effort. The proposed method's superiority is confirmed by experimental results, which demonstrate high prediction accuracy and rapid response under various operating conditions. These qualities make the method highly suitable for real-time, high-precision, and miniaturized applications such as small robotic joints driven by USMs and precise medical machines.

关键词： Ultrasonic motors Torque control Long short-term memory network Attention mechanism differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

A Q-learning improved differential evolution algorithm for human-centric dynamic distributed flexible job shop scheduling problem

引用

JOURNAL OF MANUFACTURING SYSTEMS 2025年 80卷 794-823页

作者： Li, Xixing Guo, Ao Yin, Xiyan Tang, Hongtao Wu, Rui Zhao, Qingqing Li, Yibing Wang, Xivincent Hubei Univ Technol Sch Mech Engn Hubei Key Lab Modern Mfg & Qual Engn Wuhan Peoples R China Wuhan Univ Technol Sch Mech & Elect Engn Wuhan Peoples R China KTH Royal Inst Technol Dept Prod Engn Stockholm Sweden

Traditional scheduling less account of human-related dynamic events: worker skill degradation and worker mandatory rest. However, in actual production, workers experience fatigue accumulation that decreases work efficiency, thereby decreasing the precision of jobs, increasing rework rates, and even elevating processing risks. It conflicts with the idea of industrial resilience and human well-being for Industry 5.0. Therefore, a humancentric dynamic distributed flexible job shop scheduling problem (HDDFJSP) has been researched in this paper. Firstly, a multi-objective mathematical model of HDDFJSP is proposed to minimize makespan, worker fatigue, and scheduling deviation. Secondly, a Q-learning improved differential evolution (QLIDE) is designed to solve the HDDFJSP. In the QLIDE, a new four-layer encoding method and two initialization strategies are proposed to generate a high-quality initial population and a novel mutation strategy and two auxiliary mutation methods are designed to enhance the algorithm's exploitation capabilities. Furthermore, three neighborhood search strategies are introduced and combined with mutation operations as part of the Q-learning action phase to improve population convergence and diversity. Thirdly comparative test with four other well-known algorithms has been conducted and the results demonstrate the significant superiority of the QLIDE. Finally, the QLIDE is applied to solve a real case of a labor intensive hydraulic cylinder manufacturing enterprise. The results indicate that considering rescheduling can effectively help production managers to handle dynamic event of humans during the intelligent manufacturing systems.

关键词： Human-Centric differential evolution algorithm Q -learning Dynamic rescheduling

来源：评论

学校读者我要写书评

暂无评论

Autonomous underwater vehicle path planning using fitness-based differential evolution algorithm

引用

JOURNAL OF COMPUTATIONAL SCIENCE 2025年 85卷

作者： Gupta, Shubham Kumar, Ayush Kumar, Vinay Singh, Shitu Sachin Gautam, Mayank Motilal Nehru Natl Inst Technol Allahabad Dept Math Prayagraj 211004 India Motilal Nehru Natl Inst Technol Allahabad Dept Elect & Commun Engn Prayagraj 211004 India United Univ Dept Appl Sci Prayagraj 211012 Uttar Pradesh India

The enhanced capabilities of autonomous underwater vehicles (AUVs) will facilitate sustainable exploration and utilization of maritime resources through improved precision in underwater mapping, resource extraction, and environmental surveillance. Enhanced navigation and communication systems will bolster the robustness and flexibility of AUVs, opening up new avenues for research and operations in demanding underwater conditions. The objective of this initiative is to optimize the performance of AUVs by developing sophisticated navigation methodologies specifically designed for complex marine environments. To achieve this goal, this paper proposes a modified structure of the well-known metaheuristic called differential evolution (DE). The proposed algorithm is denoted by a fitness-based differential evolution algorithm (FDE). Through the utilization of path planning techniques and the application of the proposed FDE to enhance navigation, this paper seeks to overcome obstacles such as underwater barriers, restricted communication, and limited visibility. These enhancements are anticipated to notably elevate the efficacy and cognitive capabilities of AUVs. The validation of the proposed FDE algorithm is conducted on nine case studies of the path planning of AUV, and the comparison is made with other metaheuristic algorithms. The comparison indicates the effectiveness of the FDE in solving the AUV path planning problem.

关键词： Autonomous underwater vehicles Underwater environment modeling Threat modeling Path finding algorithm differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

A modified Hammerstein modeling by the differential evolution algorithm

引用

SIGNAL IMAGE AND VIDEO PROCESSING 2024年第6-7期18卷 5099-5112页

作者： Chang, Wei-Der Shu Te Univ Dept Comp & Commun Kaohsiung 824 Taiwan

This paper focuses on the nonlinear system modeling based on using a modified Hammerstein system model. The proposed Hammerstein structure is composed of a bilinear neural network (BNN) and a recursive digital system in the cascaded form. The former is taken to be the nonlinear function part of the Hammerstein model, and the latter is used as the linear dynamic subsystem. The BNN is then constructed by the bilinear digital system and the recurrent neural network, which already possesses a satisfactory modeling capacity. To update all of adjustable parameters within the proposed Hammerstein model, a popular and powerful evolutionary computation called the differential evolution (DE) is utilized so that the model output can be closely to the actual nonlinear system output. Finally, a simulated nonlinear chemical process system, continuously stirred tank reactor (CSTR), is illustrated with the modeling phase and testing phase. Some experiment results as compared with another method from the subject literature are provided to demonstrate the feasibility of the proposed method and its good modeling.

关键词： Bilinear neural network Recursive digital system Hammerstein model differential evolution algorithm System modeling

来源：评论

学校读者我要写书评

暂无评论

A multi-strategy self-adaptive differential evolution algorithm for assembly hybrid flowshop lot-streaming scheduling with component sharing

引用

SWARM AND evolutionARY COMPUTATION 2025年 92卷

作者： Lu, Yiling Tang, Qiuhua Yu, Shujun Cheng, Lixin Wuhan Univ Sci & Technol Minist Educ Key Lab Met Equipment & Control Technol Wuhan Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Peoples R China

Lot-streaming helps to achieve a more balanced utilization of parallel machines and more timely assembly of components, while component sharing increases the flexibility and commonality of assembly operations. Thus, this work addresses an assembly hybrid flowshop lot-streaming scheduling problem with component sharing. A mixed-integer linear programming model is formulated to scrutinize the coupling relations among variables i.e. sub-lot splitting, machine allocation, processing sequencing, and assembly sequencing, and to minimize the maximum completion time and work-in-process inventory lexicographically. To solve the above problem efficiently, a multi-strategy self-adaptive differential evolution (MSDE) algorithm is developed. In MSDE, three problem-specific strategies that consider component integrity and specific requirements of production and assembly are integrated to enhance the initial population in terms of diversity and solution quality. A Q-learningbased selection mechanism is proposed to self-adaptively select an appropriate combination from mutation and crossover operators for achieving a balance between exploration and exploitation. An inventory reduction strategy is appended to largely reduce work-in-process components without extending completion time. Four conclusions are drawn from extensive experiments: (1) The ensemble of three population initialization strategies is superior to each individual one;(2) The Q-learning-based optimizer selection is more effective and robust than the single optimizer-based one;(3) The work-in-process inventory reduction strategy demonstrates remarkable effectiveness for most solutions;(4) MSDE outperforms the existing state-of-the-art algorithms in most cases.

关键词： Assembly flowshops Lot-streaming Component sharing differential evolution algorithm

来源：评论

学校读者我要写书评

暂无评论

An improved differential evolution algorithm for multi-modal multiobjective optimization

引用

PEERJ COMPUTER SCIENCE 2024年 10卷 e1839页

作者： Qu, Dan Xiao, Hualin Chen, Huafei Li, Hongyi China West Normal Univ Coll Math Educ Nanchong Peoples R China Sichuan Univ Sci & Engn Coll Math & Stat Zigong Peoples R China

Multi -modal multi -objective problems (MMOPs) have gained much attention during the last decade. These problems have two or more global or local Pareto optimal sets (PSs), some of which map to the same Pareto front (PF). This article presents a new affinity propagation clustering (APC) method based on the Multi -modal multiobjective differential evolution (MMODE) algorithm, called MMODE_AP, for the suit of CEC'2020 benchmark functions. First, two adaptive mutation strategies are adopted to balance exploration and exploitation and improve the diversity in the evolution process. Then, the affinity propagation clustering method is adopted to define the crowding degree in decision space (DS) and objective space (OS). Meanwhile, the non -dominated sorting scheme incorporates a particular crowding distance to truncate the population during the environmental selection process, which can obtain welldistributed solutions in both DS and OS. Moreover, the local PF membership of the solution is defined, and a predefined parameter is introduced to maintain of the local PSs and solutions around the global PS. Finally, the proposed algorithm is implemented on the suit of CEC'2020 benchmark functions for comparison with some MMODE algorithms. According to the experimental study results, the proposed MMODE_AP algorithm has about 20 better performance results on benchmark functions compared to its competitors in terms of reciprocal of Pareto sets proximity (rPSP), inverted generational distances (IGD) in the decision (IGDX) and objective (IGDF). The proposed algorithm can efficiently achieve the two goals, i.e., the convergence to the true local and global Pareto fronts along with better distributed Pareto solutions on the Pareto fronts.

关键词： differential evolution algorithm Affinity propagation Multi-modal multi-objective optimization

来源：评论

学校读者我要写书评

暂无评论

Optimizing electric vehicle routing with nonlinear charging and time windows using improved differential evolution algorithm

引用

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2024年第4期27卷 5423-5458页

作者： Deng, Jiawen Zhang, Jihui Yang, Shengxiang Qingdao Univ Sch Automat Qingdao 266071 Peoples R China Shandong Key Lab Ind Control Technol Qingdao 266071 Peoples R China De Montfort Univ Ctr Computat Intelligence Sch Comp Sci & Informat Leicester LE1 9BH Leics England

In real-life, green logistics is prevalent with the advent of pollution reduction;therefore, electric vehicle routing problem (EVRP) gains more focus. However, nonlinear charging technique has not obtained adequate attention for EVRP with time windows. In this study, an improved differential evolution (IDE) algorithm is introduced to address a variant of EVRP, which involves time windows and partial recharging policy with nonlinear charging. In IDE, a productive approach is developed to instruct the electric vehicle to charge in advance. A modified crossover operator is proposed to make populations more diverse. Five local neighborhood operators and a simulated annealing algorithm are embedded to enhance search quality. Further, we generate 55 instances based on Solomon benchmark and Analysis of Variance is leveraged to manifest the efficacy. Similarly, three algorithms are selected for comparison, i.e., genetic algorithm, artificial bee colony algorithm, and adaptive large neighborhood search. Experimental comparisons reveal that IDE outperforms others.

关键词： Electric vehicle Scheduling differential evolution algorithm Routing

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：