ISA transactions最新文献_第4页

Intermittent control for nonlinear hybrid stochastic delayed systems with measurement error via dynamic event-triggered mechanism. 带有测量误差的非线性混合随机时滞系统的动态事件触发机制间歇控制。

ISA transactions Pub Date : 2025-05-05 DOI: 10.1016/j.isatra.2025.05.005

Hairui Zhao, Dongyan Chen, Jun Hu

引用次数: 0

Sparse grey forecasting model learning and applications to fatigue life prediction of aircraft lap joint structures. 稀疏灰色预测模型学习及其在飞机搭接结构疲劳寿命预测中的应用。

ISA transactions Pub Date : 2025-05-05 DOI: 10.1016/j.isatra.2025.05.003

Lu Yang, Qiuhui Xu, Baolei Wei, Naiming Xie, Shenfang Yuan

{"title":"Sparse grey forecasting model learning and applications to fatigue life prediction of aircraft lap joint structures.","authors":"Lu Yang, Qiuhui Xu, Baolei Wei, Naiming Xie, Shenfang Yuan","doi":"10.1016/j.isatra.2025.05.003","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.05.003","url":null,"abstract":"A key challenge in the study of grey forecasting models is model structure discovery: converting measurement data into equations that are not only predictive, but provide a deeper understanding of the underlying dynamics inherent in the observations. The predominant approach relies on the cumulative sum operator, a knowledge-based technique that requires a well-characterized shape and extensive empirical experience. In this work, we propose a paradigm for data-driven modelling that simultaneously learns the structures of grey forecasting models and estimates the measurement noise at each observation. First, in the context of a state-space framework utilizing the integral representation of the grey model as a state equation, a candidate feature library is designed to explicitly depict the model equation, likely in a redundant form, and solved by sparse learning. Then, by combining signal-noise decomposition and time-stepping constraints, a regularized objective function is formulated to jointly learn model structure and noise. Next, large-scale simulations are designed to investigate the finite sample performance of the proposed method, including model structural identification accuracy, forecasting accuracy, and denoising capability. The results demonstrate high accuracy in model structure learning and robustness to measurement noise. Finally, we conduct fatigue testing on aircraft lap joints to collect crack propagation data. The proposed method is then applied to uncover dynamic patterns in the evolution of fatigue cracks and predict the remaining useful life of aircraft lap joint structures.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144059058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A dynamic utopia point updating strategy for multi-objective optimization. 多目标优化的动态乌托邦点更新策略。

ISA transactions Pub Date : 2025-05-04 DOI: 10.1016/j.isatra.2025.04.030

Yue-Yan Niu, Xiao-Jian Li

{"title":"A dynamic utopia point updating strategy for multi-objective optimization.","authors":"Yue-Yan Niu, Xiao-Jian Li","doi":"10.1016/j.isatra.2025.04.030","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.04.030","url":null,"abstract":"Multi-objective optimization problems widely exist in engineering practice, which are usually solved by repeatedly searching Pareto fronts. However, the search process faces the challenges of heavy computational burden and local optimality. To overcome these difficulties, a novel utopia optimization method is developed in the paper, where the multi-objective problems are converted into single-objective ones without repeatedly searching, and then the computational burden is reduced. In particular, different from the classical utopia optimization, where the utopia point is always fixed during the whole optimization process, a dynamical updating strategy is proposed by comparing the current optimization solution and the original utopia point, and the local optimality problem is also solved. Moreover, an improved particle swarm optimization method with the Logistic map and adaptive weights is developed to further enhance the computing ability of the optimization solution. Finally, three examples are taken for simulations, and the results indicate that the relative errors between the global optimums and the optimal values are respectively reduced by 1.45, 1.06, and 0.14, compared with the existing approaches.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144015493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimal control of PVC polymerization process with set values based on TD3 algorithm. 基于TD3算法的聚氯乙烯聚合过程设定值优化控制。

ISA transactions Pub Date : 2025-05-03 DOI: 10.1016/j.isatra.2025.04.023

Shuzhi Gao, Qing Liu, Shiwei Yang, Qiang Wang

引用次数: 0

Learning observer-based fault-tolerant control for semi-Markov jumping systems with probabilistic-memory event-triggered protocol. 基于学习观测器的概率记忆事件触发协议半马尔可夫跳跃系统容错控制。

ISA transactions Pub Date : 2025-05-02 DOI: 10.1016/j.isatra.2025.04.025

Qilong Xie, Yunliang Wang, Jun Cheng, Dan Zhang, Wenhai Qi

引用次数: 0

Impact analysis of capacitive energy storage integration on load frequency control performance of microgrids employing a new dual-stage controller. 采用新型双级控制器的电容储能集成对微电网负荷频率控制性能的影响分析。

ISA transactions Pub Date : 2025-05-02 DOI: 10.1016/j.isatra.2025.04.003

Bhuvnesh Khokhar, Krishna Pal Singh Parmar

{"title":"Impact analysis of capacitive energy storage integration on load frequency control performance of microgrids employing a new dual-stage controller.","authors":"Bhuvnesh Khokhar, Krishna Pal Singh Parmar","doi":"10.1016/j.isatra.2025.04.003","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.04.003","url":null,"abstract":"A microgrid (MG) with inherent low inertia and renewable energy sources (RES)-based generators may encounter difficulties in maintaining frequency stability due to load changes. In order to mitigate frequency stability concerns, it is imperative to use energy storage units (ESUs). Objective of this study is to analyze the impact of capacitive energy storage unit (CESU) integration on the load frequency control (LFC) performance of two distinct MG systems. A new dual-stage PIλ-(1+PDμF) controller is proposed as a secondary controller for the LFC study. Parameters of the controller are optimized employing a recently developed arithmetic optimization algorithm (AOA). Performance of the suggested control approach is evaluated against several standard control approaches. Simulation findings demonstrate that with CESU integration the suggested controller markedly enhances frequency and tie-line power deviation responses and their transient characteristics for both the MG systems. A maximum improvement of 98.50% in peak overshoot, 94.88% in peak undershoot, and 77.18% in settling time is observed with the suggested control approach. This study further justifies the robustness of the proposed control approach against the MG systems parameter variations, impact of CESU integration through statistical analysis, small signal stability of both the MG systems, and convergence performance of the AOA.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144046272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Safe prescribed time controller for wheeled mobile robots by using control barrier functions as a safety filter. 采用控制屏障函数作为安全滤波器的轮式移动机器人安全规定时间控制器。

ISA transactions Pub Date : 2025-05-02 DOI: 10.1016/j.isatra.2025.04.024

Ali Alavi Nasab, Roozbeh Badiei, Mohammad Hassan Asemani

引用次数: 0

An event-triggered deep reinforcement learning guidance algorithm for intercepting maneuvering target of speed advantage. 针对速度优势机动目标的事件触发深度强化学习制导算法。

ISA transactions Pub Date : 2025-04-30 DOI: 10.1016/j.isatra.2025.04.035

Xu Wang, Yifan Deng, Yuanli Cai, Haonan Jiang

{"title":"An event-triggered deep reinforcement learning guidance algorithm for intercepting maneuvering target of speed advantage.","authors":"Xu Wang, Yifan Deng, Yuanli Cai, Haonan Jiang","doi":"10.1016/j.isatra.2025.04.035","DOIUrl":"https://doi.org/10.1016/j.isatra.2025.04.035","url":null,"abstract":"Hypersonic vehicle interception raises stringent and challenging requirements for traditional guidance laws in terms of speed and maneuverability advantage. Deep reinforcement learning algorithms provide potential solutions for intercepting maneuvering targets of speed advantage, but they are greatly hindered by policy training inefficiency. To address these limitations, we propose a novel event-triggered deep reinforcement learning (ETDRL) algorithm along with an event-triggered training and time-triggered execution (ETTE) framework. The ETTE framework reformulates the agent-environment interaction as an event-triggered Markov decision process (ETMDP) model, where the agent updates its action only when the environment state meets a specific event triggering condition, otherwise maintaining the previous behavior between events. As a result, this approach significantly accelerates policy training by reducing the total number of decision steps required during the learning phase. To mitigate the potential degradation in control performance caused by the event-triggered mechanism, the ETTE framework enables well-trained policies to be executed with a fixed decision interval, that is, in a time-triggered way. Based on the proposed method, an ETDRL guidance law is developed for intercepting maneuvering targets of speed advantage under constraints of limited maneuverability, large initial heading error, and bearings-only measurement. By following the design principle of nullifying the line-of-sight angular rate to establish a collision course with the target, we model the guidance problem as an ETMDP. The twin delayed deep deterministic policy gradient algorithm is utilized to train the ETDRL guidance law. Numerical simulations demonstrate the superiority of the proposed ETDRL method over DRL algorithms in terms of policy training efficiency, while also highlighting its enhanced guidance performance over traditional methods.","PeriodicalId":94059,"journal":{"name":"ISA transactions","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144047279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Learning-based MPC of sampled-data systems with partially unknown dynamics. 部分未知动态的采样数据系统的基于学习的MPC。

ISA transactions Pub Date : 2025-04-30 DOI: 10.1016/j.isatra.2025.04.028

Seungyong Han, Xuyang Guo, Suneel Kumar Kommuri

引用次数: 0

Prescribed-time adaptive event-triggered control for robot manipulators based on command filtering. 基于命令滤波的机器人操作臂定时自适应事件触发控制。

ISA transactions Pub Date : 2025-04-30 DOI: 10.1016/j.isatra.2025.04.021

Yongling Xia, Yanbin Liu, Weichao Sun

引用次数: 0