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Cubature Kalman Fusion Filtering Under Amplify- and-Forward Relays With Randomly Varying Channel Parameters
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124590
Jiaxing Li;Zidong Wang;Jun Hu;Hongli Dong;Hongjian Liu
{"title":"Cubature Kalman Fusion Filtering Under Amplify- and-Forward Relays With Randomly Varying Channel Parameters","authors":"Jiaxing Li;Zidong Wang;Jun Hu;Hongli Dong;Hongjian Liu","doi":"10.1109/JAS.2024.124590","DOIUrl":"https://doi.org/10.1109/JAS.2024.124590","url":null,"abstract":"In this paper, the problem of cubature Kalman fusion filtering (CKFF) is addressed for multi-sensor systems under amplify-and-forward (AaF) relays. For the purpose of facilitating data transmission, AaF relays are utilized to regulate signal communication between sensors and filters. Here, the randomly varying channel parameters are represented by a set of stochastic variables whose occurring probabilities are permitted to exhibit bounded uncertainty. Employing the spherical-radial cubature principle, a local filter under AaF relays is initially constructed. This construction ensures and minimizes an upper bound of the filtering error covariance by designing an appropriate filter gain. Subsequently, the local filters are fused through the application of the covariance intersection fusion rule. Furthermore, the uniform boundedness of the filtering error covariance's upper bound is investigated through establishing certain sufficient conditions. The effectiveness of the proposed CKFF scheme is ultimately validated via a simulation experiment concentrating on a three-phase induction machine.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"356-368"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106674","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
Value Iteration-Based Distributed Adaptive Dynamic Programming for Multi-Player Differential Game with Incomplete Information
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124950
Yun Zhang;Yuqi Wang;Yunze Cai
{"title":"Value Iteration-Based Distributed Adaptive Dynamic Programming for Multi-Player Differential Game with Incomplete Information","authors":"Yun Zhang;Yuqi Wang;Yunze Cai","doi":"10.1109/JAS.2024.124950","DOIUrl":"https://doi.org/10.1109/JAS.2024.124950","url":null,"abstract":"In this paper, a distributed adaptive dynamic programming (ADP) framework based on value iteration is proposed for multi-player differential games. In the game setting, players have no access to the information of others' system parameters or control laws. Each player adopts an on-policy value iteration algorithm as the basic learning framework. To deal with the incomplete information structure, players collect a period of system trajectory data to compensate for the lack of information. The policy updating step is implemented by a nonlinear optimization problem aiming to search for the proximal admissible policy. Theoretical analysis shows that by adopting proximal policy searching rules, the approximated policies can converge to a neighborhood of equilibrium policies. The efficacy of our method is illustrated by three examples, which also demonstrate that the proposed method can accelerate the learning process compared with the centralized learning framework.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"436-447"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106698","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
Neural Tucker Factorization
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124977
Peng Tang;Xin Luo
{"title":"Neural Tucker Factorization","authors":"Peng Tang;Xin Luo","doi":"10.1109/JAS.2024.124977","DOIUrl":"https://doi.org/10.1109/JAS.2024.124977","url":null,"abstract":"This letter presents a novel latent factorization model for high dimensional and incomplete (HDI) tensor, namely the neural Tucker factorization (NeuTucF), which is a generic neural network-based latent-factorization-of-tensors model under the Tucker decomposition framework. It first interprets the traditional Tucker framework into a neural network with embeddings for different tensor modes. Afterwards, a Tucker interaction layer is innovatively built to accurately represent the complex spatiotemporal feature interactions among different tensor modes. Experiments on real-world datasets demonstrate that the proposed NeuTucF model significantly outperforms several state-of-the-art models in terms of estimation accuracy to missing data in an HDI tensor, owing to its ability of accurately representing an HDI tensor via modeling the complex interaction among different input modes. Interestingly, the results also indicate that our model has a certain level of implicit regularization.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"475-477"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10846955","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Penalty Function-Based Distributed Primal-Dual Algorithm for Nonconvex Optimization Problem
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124935
Xiasheng Shi;Changyin Sun
{"title":"Penalty Function-Based Distributed Primal-Dual Algorithm for Nonconvex Optimization Problem","authors":"Xiasheng Shi;Changyin Sun","doi":"10.1109/JAS.2024.124935","DOIUrl":"https://doi.org/10.1109/JAS.2024.124935","url":null,"abstract":"This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the p-power transformation and penalty function techniques are introduced to reframe the nonconvex optimization problem. This ensures that the Hessian matrix of the augmented Lagrangian function becomes local positive definite by choosing appropriate control parameters. A multi-timescale primal-dual method is then devised based on the Karush-Kuhn-Tucker (KKT) point of the reformulated nonconvex problem to attain convergence. The Lyapunov theory guarantees the model's stability in the presence of an undirected and connected communication network. Finally, two nonconvex optimization problems are presented to demonstrate the efficacy of the previously developed method.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"394-402"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106676","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
Residential Energy Scheduling With Solar Energy Based on Dyna Adaptive Dynamic Programming
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124809
Kang Xiong;Qinglai Wei;Hongyang Li
{"title":"Residential Energy Scheduling With Solar Energy Based on Dyna Adaptive Dynamic Programming","authors":"Kang Xiong;Qinglai Wei;Hongyang Li","doi":"10.1109/JAS.2024.124809","DOIUrl":"https://doi.org/10.1109/JAS.2024.124809","url":null,"abstract":"Learning-based methods have become mainstream for solving residential energy scheduling problems. In order to improve the learning efficiency of existing methods and increase the utilization of renewable energy, we propose the Dyna action-dependent heuristic dynamic programming (Dyna-ADHDP) method, which incorporates the ideas of learning and planning from the Dyna framework in action-dependent heuristic dynamic programming. This method defines a continuous action space for precise control of an energy storage system and allows online optimization of algorithm performance during the real-time operation of the residential energy model. Meanwhile, the target network is introduced during the training process to make the training smoother and more efficient. We conducted experimental comparisons with the benchmark method using simulated and real data to verify its applicability and performance. The results confirm the method's excellent performance and generalization capabilities, as well as its excellence in increasing renewable energy utilization and extending equipment life.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"403-413"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106677","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
Soft Resource Slicing for Industrial Mixed Traffic in 5G Networks
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124761
Jingfang Ding;Meng Zheng;Haibin Yu
{"title":"Soft Resource Slicing for Industrial Mixed Traffic in 5G Networks","authors":"Jingfang Ding;Meng Zheng;Haibin Yu","doi":"10.1109/JAS.2024.124761","DOIUrl":"https://doi.org/10.1109/JAS.2024.124761","url":null,"abstract":"This letter proposes a dynamic switching soft slicing strategy for industrial mixed traffic in 5G networks. Considering two types of traffic, periodic delay-sensitive (PDS) traffic and sporadic delay-tolerant (SDT) traffic, we design a dynamic switching strategy based on a traffic-QoS-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme. The proposed strategy ensures the reliability of PDS traffic under delay constraints, while dynamically allocating remaining resources to SDT traffic. Simulation results show that the proposed soft slicing strategy out-performs existing works in meeting the strict QoS requirements of industrial mixed traffic.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"463-465"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10846933","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
DI-YOLOv5: An Improved Dual-Wavelet-Based YOLOv5 for Dense Small Object Detection
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.124368
Zi-Xin Li;Yu-Long Wang;Fei Wang
{"title":"DI-YOLOv5: An Improved Dual-Wavelet-Based YOLOv5 for Dense Small Object Detection","authors":"Zi-Xin Li;Yu-Long Wang;Fei Wang","doi":"10.1109/JAS.2024.124368","DOIUrl":"https://doi.org/10.1109/JAS.2024.124368","url":null,"abstract":"This letter focuses on the fact that small objects with few pixels disappear in feature maps with large receptive fields, as the network deepens, in object detection tasks. Therefore, the detection of dense small objects is challenging. A DI-YOLOv5 object detection algorithm is proposed. Specifically, a dual-wavelet convolution module (DWCM), which contains DWT_Conv and IWT_Conv, is proposed to reduce the loss of feature map information while obtaining feature maps with a large receptive field. The DWT _ Conv and IWT _ Conv can be used as replacements for downsampling and upsampling operations. Moreover, in the process of information transmission to the deep layer, a CSPCoA module is proposed to further capture the location information and information dependencies in different spatial directions. DWCM and CSPCoA are single, generic, plug-and-play units. We propose DI-YOLOv5 with YOLOv5 [1] as the baseline, and extensively evaluate the performance of these two modules on small object detection. Experiments demonstrate that DI-YOLOv5 can effectively improve the accuracy of object detection.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"457-459"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10846924","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106574","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Decentralized Federated Learning Algorithm Under Adversary Eavesdropping
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2025-01-20 DOI: 10.1109/JAS.2024.125079
Lei Xu;Danya Xu;Xinlei Yi;Chao Deng;Tianyou Chai;Tao Yang
{"title":"Decentralized Federated Learning Algorithm Under Adversary Eavesdropping","authors":"Lei Xu;Danya Xu;Xinlei Yi;Chao Deng;Tianyou Chai;Tao Yang","doi":"10.1109/JAS.2024.125079","DOIUrl":"https://doi.org/10.1109/JAS.2024.125079","url":null,"abstract":"In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy. In classical federated learning, the communication channel between the devices poses a potential risk of compromising private information. To reduce the risk of adversary eavesdropping in the communication channel, we propose TRADE (transmit difference weight) concept. This concept replaces the decentralized federated learning algorithm's transmitted weight parameters with differential weight parameters, enhancing the privacy data against eavesdropping. Subsequently, by integrating the TRADE concept with the primal-dual stochastic gradient descent (SGD) algorithm, we propose a decentralized TRADE primal-dual SGD algorithm. We demonstrate that our proposed algorithm's convergence properties are the same as those of the primal-dual SGD algorithm while providing enhanced privacy protection. We validate the algorithm's performance on fault diagnosis task using the Case Western Reserve University dataset, and image classification tasks using the CIFAR-10 and CIFAR-100 datasets, revealing model accuracy comparable to centralized federated learning. Additionally, the experiments confirm the algorithm's privacy protection capability.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 2","pages":"448-456"},"PeriodicalIF":15.3,"publicationDate":"2025-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143106699","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 Self-Healing Predictive Control Method for Discrete-Time Nonlinear Systems
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-12-24 DOI: 10.1109/JAS.2024.124620
Shulei Zhang;Runda Jia
{"title":"A Self-Healing Predictive Control Method for Discrete-Time Nonlinear Systems","authors":"Shulei Zhang;Runda Jia","doi":"10.1109/JAS.2024.124620","DOIUrl":"https://doi.org/10.1109/JAS.2024.124620","url":null,"abstract":"In this work, a self-healing predictive control method for discrete-time nonlinear systems is presented to ensure the system can be safely operated under abnormal states. First, a robust MPC controller for the normal case is constructed, which can drive the system to the equilibrium point when the closed-loop states are in the predetermined safe set. In this controller, the tubes are built based on the incremental Lyapunov function to tighten nominal constraints. To deal with the infeasible controller when abnormal states occur, a self-healing predictive control method is further proposed to realize self-healing by driving the system towards the safe set. This is achieved by an auxiliary soft-constrained recovery mechanism that can solve the constraint violation caused by the abnormal states. By extending the discrete-time robust control barrier function theory, it is proven that the auxiliary problem provides a predictive control barrier bounded function to make the system asymptotically stable towards the safe set. The theoretical properties of robust recursive feasibility and bounded stability are further analyzed. The efficiency of the proposed controller is verified by a numerical simulation of a continuous stirred-tank reactor process.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 4","pages":"668-682"},"PeriodicalIF":15.3,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143740231","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
PromptFusion: Harmonized Semantic Prompt Learning for Infrared and Visible Image Fusion
IF 15.3 1区 计算机科学
Ieee-Caa Journal of Automatica Sinica Pub Date : 2024-12-24 DOI: 10.1109/JAS.2024.124878
Jinyuan Liu;Xingyuan Li;Zirui Wang;Zhiying Jiang;Wei Zhong;Wei Fan;Bin Xu
{"title":"PromptFusion: Harmonized Semantic Prompt Learning for Infrared and Visible Image Fusion","authors":"Jinyuan Liu;Xingyuan Li;Zirui Wang;Zhiying Jiang;Wei Zhong;Wei Fan;Bin Xu","doi":"10.1109/JAS.2024.124878","DOIUrl":"https://doi.org/10.1109/JAS.2024.124878","url":null,"abstract":"The goal of infrared and visible image fusion (IVIF) is to integrate the unique advantages of both modalities to achieve a more comprehensive understanding of a scene. However, existing methods struggle to effectively handle modal disparities, resulting in visual degradation of the details and prominent targets of the fused images. To address these challenges, we introduce PromptFusion, a prompt-based approach that harmoniously combines multi-modality images under the guidance of semantic prompts. Firstly, to better characterize the features of different modalities, a contourlet autoencoder is designed to separate and extract the high-/low-frequency components of different modalities, thereby improving the extraction of fine details and textures. We also introduce a prompt learning mechanism using positive and negative prompts, leveraging Vision-Language Models to improve the fusion model's understanding and identification of targets in multi-modality images, leading to improved performance in downstream tasks. Furthermore, we employ bi-level asymptotic convergence optimization. This approach simplifies the intricate non-singleton non-convex bi-level problem into a series of convergent and differentiable single optimization problems that can be effectively resolved through gradient descent. Our approach advances the state-of-the-art, delivering superior fusion quality and boosting the performance of related downstream tasks. Project page: https://github.com/hey-it-s-me/PromptFusion.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"12 3","pages":"502-515"},"PeriodicalIF":15.3,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143535534","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
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