Journal of Automation and Intelligence最新文献

{"title":"Exponential stabilization of linear systems with feedback optimization and its application to microgrids control","authors":"Xiemin Mo,&nbsp;Tao Liu","doi":"10.1016/j.jai.2024.07.002","DOIUrl":"10.1016/j.jai.2024.07.002","url":null,"abstract":"<div><p>This paper proposes a feedback-optimization-based control method for linear time-invariant systems, which is aimed to exponentially stabilize the system and, meanwhile, drive the system output to an approximate solution of an optimization problem with convex set constraints and affine inequality constraints. To ensure the exponential stability of the closed-loop system, the original optimization problem is first reformulated into a counterpart that has only convex set constraints. It is shown that the optimal solution of the new optimization problem is an approximate optimal solution of the original problem. Then, based on this new optimization problem, the projected primal–dual gradient dynamics algorithm is used to design the controller. By using the singular perturbation method, sufficient conditions are provided to ensure the exponential stability of the closed-loop system. The proposed method is also applied to microgrid control.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 185-190"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000303/pdfft?md5=b50afbf5c80d148cecd77770d25cb149&pid=1-s2.0-S2949855424000303-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141704261","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}

{"title":"ConGCNet: Convex geometric constructive neural network for Industrial Internet of Things","authors":"Jing Nan ,&nbsp;Wei Dai ,&nbsp;Chau Yuen ,&nbsp;Jinliang Ding","doi":"10.1016/j.jai.2024.07.004","DOIUrl":"10.1016/j.jai.2024.07.004","url":null,"abstract":"<div><p>The intersection of the Industrial Internet of Things (IIoT) and artificial intelligence (AI) has garnered ever-increasing attention and research interest. Nevertheless, the dilemma between the strict resource-constrained nature of IIoT devices and the extensive resource demands of AI has not yet been fully addressed with a comprehensive solution. Taking advantage of the lightweight constructive neural network (LightGCNet) in developing fast learner models for IIoT, a convex geometric constructive neural network with a low-complexity control strategy, namely, ConGCNet, is proposed in this article via convex optimization and matrix theory, which enhances the convergence rate and reduces the computational consumption in comparison with LightGCNet. Firstly, a low-complexity control strategy is proposed to reduce the computational consumption during the hidden parameters training process. Secondly, a novel output weights evaluated method based on convex optimization is proposed to guarantee the convergence rate. Finally, the universal approximation property of ConGCNet is proved by the low-complexity control strategy and convex output weights evaluated method. Simulation results, including four benchmark datasets and the real-world ore grinding process, demonstrate that ConGCNet effectively reduces computational consumption in the modelling process and improves the model’s convergence rate.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 3","pages":"Pages 169-175"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000327/pdfft?md5=6981fac66e625428128ac9ad415f5fca&pid=1-s2.0-S2949855424000327-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141846488","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}

{"title":"Actuator and sensor fault isolation in a class of nonlinear dynamical systems","authors":"Hamed Tirandaz,&nbsp;Christodoulos Keliris,&nbsp;Marios M. Polycarpou","doi":"10.1016/j.jai.2024.03.001","DOIUrl":"10.1016/j.jai.2024.03.001","url":null,"abstract":"<div><p>Fault isolation in dynamical systems is a challenging task due to modeling uncertainty and measurement noise, interactive effects of multiple faults and fault propagation. This paper proposes a unified approach for isolation of multiple actuator or sensor faults in a class of nonlinear uncertain dynamical systems. Actuator and sensor fault isolation are accomplished in two independent modules, that monitor the system and are able to isolate the potential faulty actuator(s) or sensor(s). For the sensor fault isolation (SFI) case, a module is designed which monitors the system and utilizes an adaptive isolation threshold on the output residuals computed via a nonlinear estimation scheme that allows the isolation of single/multiple faulty sensor(s). For the actuator fault isolation (AFI) case, a second module is designed, which utilizes a learning-based scheme for adaptive approximation of faulty actuator(s) and, based on a reasoning decision logic and suitably designed AFI thresholds, the faulty actuator(s) set can be determined. The effectiveness of the proposed fault isolation approach developed in this paper is demonstrated through a simulation example.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 57-72"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000157/pdfft?md5=bce6563208debb4fdce8bd5316ed1f38&pid=1-s2.0-S2949855424000157-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140268312","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}

{"title":"A survey on multi-agent reinforcement learning and its application","authors":"Zepeng Ning,&nbsp;Lihua Xie","doi":"10.1016/j.jai.2024.02.003","DOIUrl":"10.1016/j.jai.2024.02.003","url":null,"abstract":"<div><p>Multi-agent reinforcement learning (MARL) has been a rapidly evolving field. This paper presents a comprehensive survey of MARL and its applications. We trace the historical evolution of MARL, highlight its progress, and discuss related survey works. Then, we review the existing works addressing inherent challenges and those focusing on diverse applications. Some representative stochastic games, MARL means, spatial forms of MARL, and task classification are revisited. We then conduct an in-depth exploration of a variety of challenges encountered in MARL applications. We also address critical operational aspects, such as hyperparameter tuning and computational complexity, which are pivotal in practical implementations of MARL. Afterward, we make a thorough overview of the applications of MARL to intelligent machines and devices, chemical engineering, biotechnology, healthcare, and societal issues, which highlights the extensive potential and relevance of MARL within both current and future technological contexts. Our survey also encompasses a detailed examination of benchmark environments used in MARL research, which are instrumental in evaluating MARL algorithms and demonstrate the adaptability of MARL to diverse application scenarios. In the end, we give our prospect for MARL and discuss their related techniques and potential future applications.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 73-91"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000042/pdfft?md5=c643163b5556ce46a4a84d8f22823a32&pid=1-s2.0-S2949855424000042-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139967098","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}

{"title":"A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems","authors":"Pingfan Liu ,&nbsp;Shaocheng Tong","doi":"10.1016/j.jai.2024.02.005","DOIUrl":"10.1016/j.jai.2024.02.005","url":null,"abstract":"<div><p>This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problem for a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuator faults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems (FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backstepping control technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme is developed under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinear UWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulation validate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 111-118"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000066/pdfft?md5=41e72e13946dd32231712f578de9b01c&pid=1-s2.0-S2949855424000066-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140465902","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}

{"title":"Large-scale self-normalizing neural networks","authors":"Zhaodong Chen ,&nbsp;Weiqin Zhao ,&nbsp;Lei Deng ,&nbsp;Yufei Ding ,&nbsp;Qinghao Wen ,&nbsp;Guoqi Li ,&nbsp;Yuan Xie","doi":"10.1016/j.jai.2024.05.001","DOIUrl":"10.1016/j.jai.2024.05.001","url":null,"abstract":"<div><p>Self-normalizing neural networks (SNN) regulate the activation and gradient flows through activation functions with the self-normalization property. As SNNs do not rely on norms computed from minibatches, they are more friendly to data parallelism, kernel fusion, and emerging architectures such as ReRAM-based accelerators. However, existing SNNs have mainly demonstrated their effectiveness on toy datasets and fall short in accuracy when dealing with large-scale tasks like ImageNet. They lack the strong normalization, regularization, and expression power required for wider, deeper models and larger-scale tasks. To enhance the normalization strength, this paper introduces a comprehensive and practical definition of the self-normalization property in terms of the stability and attractiveness of the statistical fixed points. It is comprehensive as it jointly considers all the fixed points used by existing studies: the first and second moment of forward activation and the expected Frobenius norm of backward gradient. The practicality comes from the analytical equations provided by our paper to assess the stability and attractiveness of each fixed point, which are derived from theoretical analysis of the forward and backward signals. The proposed definition is applied to a meta activation function inspired by prior research, leading to a stronger self-normalizing activation function named “bi-scaled exponential linear unit with backward standardized” (bSELU-BSTD). We provide both theoretical and empirical evidence to show that it is superior to existing studies. To enhance the regularization and expression power, we further propose scaled-Mixup and channel-wise scale &amp; shift. With these three techniques, our approach achieves <strong>75.23%</strong> top-1 accuracy on the ImageNet with Conv MobileNet V1, surpassing the performance of existing self-normalizing activation functions. To the best of our knowledge, this is the first SNN that achieves comparable accuracy to batch normalization on ImageNet.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 101-110"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000194/pdfft?md5=336e35816fb9708e5d5bbfc6ba5ac066&pid=1-s2.0-S2949855424000194-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141143515","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}

{"title":"Event-triggered robust cooperative output regulation for a class of linear multi-agent systems with an unknown exosystem","authors":"Yangyang Qian ,&nbsp;Lu Liu","doi":"10.1016/j.jai.2024.03.004","DOIUrl":"10.1016/j.jai.2024.03.004","url":null,"abstract":"<div><p>This paper investigates the robust cooperative output regulation problem for a class of heterogeneous uncertain linear multi-agent systems with an unknown exosystem via event-triggered control (ETC). By utilizing the internal model approach and the adaptive control technique, a distributed adaptive internal model is constructed for each agent. Then, based on this internal model, a fully distributed ETC strategy composed of a distributed event-triggered adaptive output feedback control law and a distributed dynamic event-triggering mechanism is proposed, in which each agent updates its control input at its own triggering time instants. It is shown that under the proposed ETC strategy, the robust cooperative output regulation problem can be solved without requiring either the global information associated with the communication topology or the bounds of the uncertain or unknown parameters in each agent and the exosystem. A numerical example is provided to illustrate the effectiveness of the proposed control strategy.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 119-127"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000182/pdfft?md5=7b1ebe07f2f5f486b5aa7e8d1ce6c2d1&pid=1-s2.0-S2949855424000182-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140405436","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}

{"title":"Robust adaptive leaderless consensus of unknown non-minimum phase linear multi-agent systems subject to disturbances and/or unmodeled dynamics","authors":"Wenji Cao,&nbsp;Gang Feng","doi":"10.1016/j.jai.2024.03.002","DOIUrl":"10.1016/j.jai.2024.03.002","url":null,"abstract":"<div><p>This article investigates the problem of robust adaptive leaderless consensus for heterogeneous uncertain non-minimum phase linear multi-agent systems over directed communication graphs. Each agent is assumed to be of unknown nominal dynamics and also subject to external disturbances and/or unmodeled dynamics. A novel distributed robust adaptive control strategy is proposed. It is shown that the robust adaptive leaderless consensus problem is solved with the proposed control strategy under some sufficient conditions. Two examples are provided to demonstrate the efficacy of the proposed control strategy.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 2","pages":"Pages 92-100"},"PeriodicalIF":0.0,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000169/pdfft?md5=3e37542ce7236b05a3f7a24569a48c15&pid=1-s2.0-S2949855424000169-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140281679","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}

{"title":"Adaptive predictor-based control for a helicopter system with input delays: Design and experiments","authors":"Siri Marte Schlanbusch,&nbsp;Jing Zhou","doi":"10.1016/j.jai.2024.02.001","DOIUrl":"10.1016/j.jai.2024.02.001","url":null,"abstract":"<div><p>In this paper, we consider a 2-degrees-of-freedom (DOF) helicopter system subject to long input delays and uncertain system parameters. To address the challenges including unknown system parameters and input delays in control design, we develop an adaptive predictor-feedback control law to achieve trajectory tracking. Stability of the closed-loop system is further established, where the tracking errors are shown to converge towards zero. Through simulation and experiments on the helicopter system, we illustrate that tracking of a desired trajectory is achieved with the proposed control scheme.</p></div>","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 1","pages":"Pages 50-56"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000029/pdfft?md5=7665415a3be78afb7ed8a62725586e3a&pid=1-s2.0-S2949855424000029-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139887210","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}

{"title":"New year with new achievements","authors":"Yongduan Song","doi":"10.1016/j.jai.2024.02.004","DOIUrl":"https://doi.org/10.1016/j.jai.2024.02.004","url":null,"abstract":"","PeriodicalId":100755,"journal":{"name":"Journal of Automation and Intelligence","volume":"3 1","pages":"Page 1"},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949855424000054/pdfft?md5=d27cc8f5b231abfb4bf3710ac8174600&pid=1-s2.0-S2949855424000054-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140160228","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}