Journal of Automation and Intelligence最新文献_第5页

Practical prescribed-time fuzzy tracking control for uncertain nonlinear systems with time-varying actuators faults 带有时变执行器故障的不确定非线性系统的实用规定时间模糊跟踪控制

Journal of Automation and Intelligence Pub Date : 2024-03-01 DOI: 10.1016/j.jai.2023.12.003

Shuxing Xuan , Hongjing Liang , Tingwen Huang

{"title":"Practical prescribed-time fuzzy tracking control for uncertain nonlinear systems with time-varying actuators faults","authors":"Shuxing Xuan , Hongjing Liang , Tingwen Huang","doi":"10.1016/j.jai.2023.12.003","DOIUrl":"https://doi.org/10.1016/j.jai.2023.12.003","url":null,"abstract":"<div><p>The paper investigates the practical prescribed-time fuzzy tracking control problem for a category of nonlinear system subject to time-varying actuator faults. The presence of unknown nonlinear dynamics and actuator faults makes achieving tracking control within a prescribed-time challenging. To tackle this issue, we propose a novel practical prescribed-time fuzzy tracking control strategy, which is independent of the initial state of the system and does not rely on precise modeling of the system and actuators. We apply the approximation capabilities of fuzzy logic systems to handle the unknown nonlinear functions and unidentified actuator faults in the system. The piecewise controller and adaptive law constructed based on piecewise prescribed time-varying function and backstepping technique method establish the theoretical framework of practical prescribed-time tracking control, and extend the range of prescribed-time tracking control to infinity. Regardless of the initial conditions, the proposed control strategy can guarantee that all signals remain uniformly bounded within the practical prescribed time in the presence of unknown nonlinear item and time-varying actuator faults. Simulation example is presented to demonstrate the effectiveness of the proposed control strategy.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 1","pages":"Pages 40-49"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294985542300059X/pdfft?md5=52a438279e20d3abf3d23f3b83fbb7fa&pid=1-s2.0-S294985542300059X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-triggered H∞ PI state estimation for delayed switched neural networks 延迟开关神经网络的事件触发 H∞ PI 状态估计

Journal of Automation and Intelligence Pub Date : 2024-03-01 DOI: 10.1016/j.jai.2024.02.002

Yuzhong Wang , Changyun Wen , Xiaolei Li

{"title":"Event-triggered H∞ PI state estimation for delayed switched neural networks","authors":"Yuzhong Wang , Changyun Wen , Xiaolei Li","doi":"10.1016/j.jai.2024.02.002","DOIUrl":"https://doi.org/10.1016/j.jai.2024.02.002","url":null,"abstract":"<div><p>On state estimation problems of switched neural networks, most existing results with an event-triggered scheme (ETS) not only ignore the estimator information, but also just employ a fixed triggering threshold, and the estimation error cannot be guaranteed to converge to zero. In addition, the state estimator of non-switched neural networks with integral and exponentially convergent terms cannot be used to improve the estimation performance of switched neural networks due to the difficulties caused by the nonsmoothness of the considered Lyapunov function at the switching instants. In this paper, we aim at overcoming such difficulties and filling in the gaps, by proposing a novel adaptive ETS (AETS) to design an event-based <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> switched proportional–integral (PI) state estimator. A triggering-dependent exponential convergence term and an integral term are introduced into the switched PI state estimator. The relationship among the average dwell time, the AETS and the PI state estimator are established by the triggering-dependent exponential convergence term such that estimation error asymptotically converges to zero with <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance level. It is shown that the convergence rate of the resultant error system can be adaptively adjusted according to triggering signals. Finally, the validity of the proposed theoretical results is verified through two illustrative examples.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 1","pages":"Pages 26-33"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000030/pdfft?md5=ca0dfc3b892317269c5114552323be59&pid=1-s2.0-S2949855424000030-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exact controllability of rational expectations model with multiplicative noise and input delay 带有乘法噪声和输入延迟的理性预期模型的精确可控性

Journal of Automation and Intelligence Pub Date : 2024-03-01 DOI: 10.1016/j.jai.2024.01.001

Wenjing Wang , Juanjuan Xu , Huanshui Zhang , Minyue Fu

引用次数: 0

Adaptive predictor-based control for a helicopter system with input delays: Design and experiments 基于自适应预测器的输入延迟直升机系统控制：设计与实验

Journal of Automation and Intelligence Pub Date : 2024-02-01 DOI: 10.1016/j.jai.2024.02.001

S. Schlanbusch, Jing Zhou

引用次数: 0

Exact controllability of rational expectations model with multiplicative noise and input delay 带有乘法噪声和输入延迟的理性预期模型的精确可控性

Journal of Automation and Intelligence Pub Date : 2024-02-01 DOI: 10.1016/j.jai.2024.01.001

Wenjing Wang, Juanjuan Xu, Huanshui Zhang, Minyue Fu

引用次数: 0

A generic framework for qualifications of digital twins in maintenance 数字孪生维护资质通用框架

Journal of Automation and Intelligence Pub Date : 2023-11-01 DOI: 10.1016/j.jai.2023.07.002

Jie Liu, Xingheng Liu, Jørn Vatn, Shen Yin

{"title":"A generic framework for qualifications of digital twins in maintenance","authors":"Jie Liu, Xingheng Liu, Jørn Vatn, Shen Yin","doi":"10.1016/j.jai.2023.07.002","DOIUrl":"10.1016/j.jai.2023.07.002","url":null,"abstract":"<div><p>Digital twins have emerged as a promising technology for maintenance applications, enabling organizations to simulate and monitor physical assets to improve their performance. In Operation and Maintenance (O&M), digital twin facilitates the diagnosis and prognosis of critical assets, forming the basis for smart maintenance planning and reducing downtime. However, there is a lack of standardized approaches for the qualifications of digital twins in maintenance, leading to low trustworthiness and limiting its application. This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars, namely fidelity, smartness, timeliness, integration, and standard compliance. We demonstrate the effectiveness of the framework through two case studies, showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance. Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently, leading to significant benefits in terms of cost reduction, performance improvement, and sustainability.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 4","pages":"Pages 196-203"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294985542300031X/pdfft?md5=a83844e12c5df9bce1296ec251ee4b59&pid=1-s2.0-S294985542300031X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81664900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Event-based performance guaranteed tracking control for constrained nonlinear system via adaptive dynamic programming method 通过自适应动态编程法实现受约束非线性系统的基于事件的性能保证跟踪控制

Journal of Automation and Intelligence Pub Date : 2023-11-01 DOI: 10.1016/j.jai.2023.11.002

Xingyi Zhang, Zijie Guo, Hongru Ren, Hongyi Li

{"title":"Event-based performance guaranteed tracking control for constrained nonlinear system via adaptive dynamic programming method","authors":"Xingyi Zhang, Zijie Guo, Hongru Ren, Hongyi Li","doi":"10.1016/j.jai.2023.11.002","DOIUrl":"10.1016/j.jai.2023.11.002","url":null,"abstract":"<div><p>An optimal tracking control problem for a class of nonlinear systems with guaranteed performance and asymmetric input constraints is discussed in this paper. The control policy is implemented by adaptive dynamic programming (ADP) algorithm under two event-based triggering mechanisms. It is often challenging to design an optimal control law due to the system deviation caused by asymmetric input constraints. First, a prescribed performance control technique is employed to guarantee the tracking errors within predetermined boundaries. Subsequently, considering the asymmetric input constraints, a discounted non-quadratic cost function is introduced. Moreover, in order to reduce controller updates, an event-triggered control law is developed for ADP algorithm. After that, to further simplify the complexity of controller design, this work is extended to a self-triggered case for relaxing the need for continuous signal monitoring by hardware devices. By employing the Lyapunov method, the uniform ultimate boundedness of all signals is proved to be guaranteed. Finally, a simulation example on a mass–spring–damper system subject to asymmetric input constraints is provided to validate the effectiveness of the proposed control scheme.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 4","pages":"Pages 239-247"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855423000473/pdfft?md5=e6a0affcc6d203edf03ab9613e063578&pid=1-s2.0-S2949855423000473-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138616887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A comprehensive survey of robust deep learning in computer vision 计算机视觉中的鲁棒深度学习综合调查

Journal of Automation and Intelligence Pub Date : 2023-11-01 DOI: 10.1016/j.jai.2023.10.002

Jia Liu , Yaochu Jin

{"title":"A comprehensive survey of robust deep learning in computer vision","authors":"Jia Liu , Yaochu Jin","doi":"10.1016/j.jai.2023.10.002","DOIUrl":"https://doi.org/10.1016/j.jai.2023.10.002","url":null,"abstract":"<div><p>Deep learning has presented remarkable progress in various tasks. Despite the excellent performance, deep learning models remain not robust, especially to well-designed adversarial examples, limiting deep learning models employed in security-critical applications. Therefore, how to improve the robustness of deep learning has attracted increasing attention from researchers. This paper investigates the progress on the threat of deep learning and the techniques that can enhance the model robustness in computer vision. Unlike previous relevant survey papers summarizing adversarial attacks and defense technologies, this paper also provides an overview of the general robustness of deep learning. Besides, this survey elaborates on the current robustness evaluation approaches, which require further exploration. This paper also reviews the recent literature on making deep learning models resistant to adversarial examples from an architectural perspective, which was rarely mentioned in previous surveys. Finally, interesting directions for future research are listed based on the reviewed literature. This survey is hoped to serve as the basis for future research in this topical field.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 4","pages":"Pages 175-195"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S294985542300045X/pdfft?md5=4ec3b4ce82d2aa24d2e48cd35edc7071&pid=1-s2.0-S294985542300045X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139050418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Consensus of networked control multi-agent systems using a double-layer encryption scheme 使用双层加密方案达成网络控制多代理系统的共识

Journal of Automation and Intelligence Pub Date : 2023-11-01 DOI: 10.1016/j.jai.2023.10.001

Yamin Yan , Zhiyong Chen , Vijay Varadharajan

引用次数: 0

Bilateral co-transfer for unsupervised domain adaptation 无监督领域适应的双边共同转移

Journal of Automation and Intelligence Pub Date : 2023-11-01 DOI: 10.1016/j.jai.2023.11.003

Fuxiang Huang , Jingru Fu , Lei Zhang

{"title":"Bilateral co-transfer for unsupervised domain adaptation","authors":"Fuxiang Huang , Jingru Fu , Lei Zhang","doi":"10.1016/j.jai.2023.11.003","DOIUrl":"https://doi.org/10.1016/j.jai.2023.11.003","url":null,"abstract":"<div><p>Labeled data scarcity of an interested domain is often a serious problem in machine learning. Leveraging the labeled data from other semantic-related yet co-variate shifted source domain to facilitate the interested domain is a consensus. In order to solve the domain shift between domains and reduce the learning ambiguity, unsupervised domain adaptation (UDA) greatly promotes the transferability of model parameters. However, the dilemma of over-fitting (negative transfer) and under-fitting (under-adaptation) is always an overlooked challenge and potential risk. In this paper, we rethink the shallow learning paradigm and this intractable over/under-fitting problem, and propose a safer UDA model, coined as Bilateral Co-Transfer (BCT), which is essentially beyond previous well-known unilateral transfer. With bilateral co-transfer between domains, the risk of over/under-fitting is therefore largely reduced. Technically, the proposed BCT is a symmetrical structure, with joint distribution discrepancy (JDD) modeled for domain alignment and category discrimination. Specifically, a symmetrical bilateral transfer (SBT) loss between source and target domains is proposed under the philosophy of <em>mutual checks and balances</em>. First, each target sample is represented by source samples with low-rankness constraint in a common subspace, such that the most informative and transferable source data can be used to alleviate negative transfer. Second, each source sample is symmetrically and sparsely represented by target samples, such that the most reliable target samples can be exploited to tackle under-adaptation. Experiments on various benchmarks show that our BCT outperforms many previous outstanding work.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"2 4","pages":"Pages 204-217"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855423000485/pdfft?md5=fb9ddfc4aec3f40f01af3c9921fe8657&pid=1-s2.0-S2949855423000485-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139050419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0