Ieee-Caa Journal of Automatica Sinica最新文献_第6页

Explainable Neural Network for Sensitivity Analysis of Lithium-Ion Battery Smart Production 用于锂离子电池智能生产敏感性分析的可解释神经网络

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-08-15 DOI: 10.1109/JAS.2024.124539

Kailong Liu;Qiao Peng;Yuhang Liu;Naxin Cui;Chenghui Zhang

{"title":"Explainable Neural Network for Sensitivity Analysis of Lithium-Ion Battery Smart Production","authors":"Kailong Liu;Qiao Peng;Yuhang Liu;Naxin Cui;Chenghui Zhang","doi":"10.1109/JAS.2024.124539","DOIUrl":"https://doi.org/10.1109/JAS.2024.124539","url":null,"abstract":"Battery production is crucial for determining the quality of electrode, which in turn affects the manufactured battery performance. As battery production is complicated with strongly coupled intermediate and control parameters, an efficient solution that can perform a reliable sensitivity analysis of the production terms of interest and forecast key battery properties in the early production phase is urgently required. This paper performs detailed sensitivity analysis of key production terms on determining the properties of manufactured battery electrode via advanced data-driven modelling. To be specific, an explainable neural network named generalized additive model with structured interaction (GAM-SI) is designed to predict two key battery properties, including electrode mass loading and porosity, while the effects of four early production terms on manufactured batteries are explained and analysed. The experimental results reveal that the proposed method is able to accurately predict battery electrode properties in the mixing and coating stages. In addition, the importance ratio ranking, global interpretation and local interpretation of both the main effects and pairwise interactions can be effectively visualized by the designed neural network. Due to the merits of interpretability, the proposed GAM-SI can help engineers gain important insights for understanding complicated production behavior, further benefitting smart battery production.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 9","pages":"1944-1953"},"PeriodicalIF":15.3,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141991510","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Scholar of Dignity: Remembering Peter Luh 有尊严的学者缅怀彼得-卢

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-08-15 DOI: 10.1109/JAS.2024.124833

Fei-Yue Wang

引用次数: 0

Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm 通过差分进化算法为非线性网络系统实现基于事件触发的新型自适应记忆模糊鲁棒控制

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-22 DOI: 10.1109/JAS.2024.124419

Wei Qian;Yanmin Wu;Bo Shen

{"title":"Novel Adaptive Memory Event-Triggered-Based Fuzzy Robust Control for Nonlinear Networked Systems via the Differential Evolution Algorithm","authors":"Wei Qian;Yanmin Wu;Bo Shen","doi":"10.1109/JAS.2024.124419","DOIUrl":"https://doi.org/10.1109/JAS.2024.124419","url":null,"abstract":"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 algorithm. To 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 data. Sufficient 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 matrices. Subsequently, under the IPM policy, a new MFs intelligent optimization technique that takes advantage of the differential evolution algorithm is first provided for IT2 Takagi-Sugeno (T-S) fuzzy systems to update the fuzzy controller MFs in real-time and achieve a better system control effect. Finally, simulation results demonstrate that the proposed control scheme can obtain better system performance in the case of using fewer communication resources.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 8","pages":"1836-1848"},"PeriodicalIF":15.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on Type-3 Fuzzy Logic Systems and Their Control Applications 第三类模糊逻辑系统及其控制应用概览

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-22 DOI: 10.1109/JAS.2024.124530

Oscar Castillo;Fevrier Valdez;Patricia Melin;Weiping Ding

{"title":"A Survey on Type-3 Fuzzy Logic Systems and Their Control Applications","authors":"Oscar Castillo;Fevrier Valdez;Patricia Melin;Weiping Ding","doi":"10.1109/JAS.2024.124530","DOIUrl":"https://doi.org/10.1109/JAS.2024.124530","url":null,"abstract":"In this paper, we offer a review of type-3 fuzzy logic systems and their applications in control. The main objective of this work is to observe and analyze in detail the applications in the control area using type-3 fuzzy logic systems. In this case, we review their most important applications in control and other related topics with type-3 fuzzy systems. Intelligent algorithms have been receiving increasing attention in control and for this reason a review in this area is important. This paper reviews the main applications that make use of Intelligent Computing methods. Specifically, type-3 fuzzy logic systems. The aim of this research is to be able to appreciate, in detail, the applications in control systems and to point out the scientific trends in the use of Intelligent Computing techniques. This is done with the construction and visualization of bibliometric networks, developed with VosViewer Software, which it is a free Java-based program, mainly intended to be used for analyzing and visualizing bibliometric networks. With this tool, we can create maps of publications, authors, or journals based on a co-citation network or construct maps of keywords, countries based on a co-occurrence networks, research groups, etc.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 8","pages":"1744-1756"},"PeriodicalIF":15.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems 用模式挖掘增强进化算法，解决稀疏的大规模多目标优化问题

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-22 DOI: 10.1109/JAS.2024.124548

Sheng Qi;Rui Wang;Tao Zhang;Weixiong Huang;Fan Yu;Ling Wang

{"title":"Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems","authors":"Sheng Qi;Rui Wang;Tao Zhang;Weixiong Huang;Fan Yu;Ling Wang","doi":"10.1109/JAS.2024.124548","DOIUrl":"https://doi.org/10.1109/JAS.2024.124548","url":null,"abstract":"Sparse large-scale multi-objective optimization problems (SLMOPs) are common in science and engineering. However, the large-scale problem represents the high dimensionality of the decision space, requiring algorithms to traverse vast expanse with limited computational resources. Furthermore, in the context of sparse, most variables in Pareto optimal solutions are zero, making it difficult for algorithms to identify non-zero variables efficiently. This paper is dedicated to addressing the challenges posed by SLMOPs. To start, we introduce innovative objective functions customized to mine maximum and minimum candidate sets. This substantial enhancement dramatically improves the efficacy of frequent pattern mining. In this way, selecting candidate sets is no longer based on the quantity of non-zero variables they contain but on a higher proportion of non-zero variables within specific dimensions. Additionally, we unveil a novel approach to association rule mining, which delves into the intricate relationships between non-zero variables. This novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function value. We extensively tested our algorithm across eight benchmark problems and four real-world SLMOPs. The results demonstrate that our approach achieves competitive solutions across various challenges.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 8","pages":"1786-1801"},"PeriodicalIF":15.3,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141964776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The First Five Years of a Phase Theory for Complex Systems and Networks 复杂系统和网络相位理论的第一个五年

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-19 DOI: 10.1109/JAS.2024.124542

Dan Wang;Wei Chen;Li Qiu

引用次数: 0

Data-Driven Adaptive Predictive Control Method With Autotuned Weighting Factor for Nonlinear Systems Using Triangular Dynamic Linearization 使用三角动态线性化的非线性系统数据驱动自适应加权系数预测控制方法

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-19 DOI: 10.1109/JAS.2023.124179

Zhong-Hua Pang;Yumo Zhang;Xueyuan Sun;Shengnan Gao;Guo-Ping Liu

引用次数: 0

Constraints Separation Based Evolutionary Multitasking for Constrained Multi-Objective Optimization Problems 基于约束分离的进化多任务处理，用于受约束的多目标优化问题

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-19 DOI: 10.1109/JAS.2024.124545

Kangjia Qiao;Jing Liang;Kunjie Yu;Xuanxuan Ban;Caitong Yue;Boyang Qu;Ponnuthurai Nagaratnam Suganthan

{"title":"Constraints Separation Based Evolutionary Multitasking for Constrained Multi-Objective Optimization Problems","authors":"Kangjia Qiao;Jing Liang;Kunjie Yu;Xuanxuan Ban;Caitong Yue;Boyang Qu;Ponnuthurai Nagaratnam Suganthan","doi":"10.1109/JAS.2024.124545","DOIUrl":"https://doi.org/10.1109/JAS.2024.124545","url":null,"abstract":"Constrained multi-objective optimization problems (CMOPs) generally contain multiple constraints, which not only form multiple discrete feasible regions but also reduce the size of optimal feasible regions, thus they propose serious challenges for solvers. Among all constraints, some constraints are highly correlated with optimal feasible regions; thus they can provide effective help to find feasible Pareto front. However, most of the existing constrained multi-objective evolutionary algorithms tackle constraints by regarding all constraints as a whole or directly ignoring all constraints, and do not consider judging the relations among constraints and do not utilize the information from promising single constraints. Therefore, this paper attempts to identify promising single constraints and utilize them to help solve CMOPs. To be specific, a CMOP is transformed into a multi-tasking optimization problem, where multiple auxiliary tasks are created to search for the Pareto fronts that only consider a single constraint respectively. Besides, an auxiliary task priority method is designed to identify and retain some high-related auxiliary tasks according to the information of relative positions and dominance relationships. Moreover, an improved tentative method is designed to find and transfer useful knowledge among tasks. Experimental results on three benchmark test suites and 11 real-world problems with different numbers of constraints show better or competitive performance of the proposed method when compared with eight state-of-the-art peer methods.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 8","pages":"1819-1835"},"PeriodicalIF":15.3,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Fault Estimation for Nonlinear Systems With Sensor Saturation and Deception Attacks Using Stochastic Communication Protocols 使用随机通信协议对传感器饱和及欺骗攻击的非线性系统进行分布式故障估计

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-19 DOI: 10.1109/JAS.2023.124161

Weiwei Sun;Xinci Gao;Lusong Ding;Xiangyu Chen

{"title":"Distributed Fault Estimation for Nonlinear Systems With Sensor Saturation and Deception Attacks Using Stochastic Communication Protocols","authors":"Weiwei Sun;Xinci Gao;Lusong Ding;Xiangyu Chen","doi":"10.1109/JAS.2023.124161","DOIUrl":"https://doi.org/10.1109/JAS.2023.124161","url":null,"abstract":"This paper is aimed at the distributed fault estimation issue associated with the potential loss of actuator efficiency for a type of discrete-time nonlinear systems with sensor saturation. For the distributed estimation structure under consideration, an estimation center is not necessary, and the estimator derives its information from itself and neighboring nodes, which fuses the state vector and the measurement vector. In an effort to cut down data conflicts in communication networks, the stochastic communication protocol (SCP) is employed so that the output signals from sensors can be selected. Additionally, a recursive security estimator scheme is created since attackers randomly inject malicious signals into the selected data. On this basis, sufficient conditions for a fault estimator with less conservatism are presented which ensure an upper bound of the estimation error covariance and the mean-square exponential boundedness of the estimating error. Finally, a numerical example is used to show the reliability and effectiveness of the considered distributed estimation algorithm.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"11 8","pages":"1865-1876"},"PeriodicalIF":15.3,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141729901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Deep Residual PLS for Data-Driven Quality Prediction Modeling in Industrial Process 用于工业流程数据驱动质量预测建模的深度残差 PLS

IF 15.3 1区计算机科学

Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-07-19 DOI: 10.1109/JAS.2024.124578

Xiaofeng Yuan;Weiwei Xu;Yalin Wang;Chunhua Yang;Weihua Gui

引用次数: 0