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Detection of Oscillations in Process Control Loops from Visual Image Space Using Deep Convolutional Networks IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-27 Tao Wang, Qiming Chen, Xun Lang, Lei Xie, Peng Li, Hongye Su
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A Novel Sensing Imaging Equipment Under Extremely Dim Light for Blast Furnace Burden Surface: Starlight High-Temperature Industrial Endoscope IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-20 Zhipeng Chen, Xinyi Wang, Weihua Gui, Jilin Zhu, Chunhua Yang, Zhaohui Jiang
Blast furnace (BF) burden surface contains the most abundant, intuitive and credible smelting information and acquiring high-definition and high-brightness optical images of which is essential to realize precise material charging control, optimize gas flow distribution and improve ironmaking efficiency. It has been challengeable to obtain high-quality optical burden surface images under high-temperature
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Designing Proportional-Integral Consensus Protocols for Second-Order Multi-Agent Systems Using Delayed and Memorized State Information IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-20 Honghai Wang, Qing-Long Han
This paper is concerned with consensus of a second-order linear time-invariant multi-agent system in the situation that there exists a communication delay among the agents in the network. A proportional-integral consensus protocol is designed by using delayed and memorized state information. Under the proportional-integral consensus protocol, the consensus problem of the multi-agent system is transformed
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A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-20 M. Victoria Luzón, Nuria Rodríguez-Barroso, Alberto Argente-Garrido, Daniel Jiménez-López, Jose M. Moyano, Javier Del Ser, Weiping Ding, Francisco Herrera
When data privacy is imposed as a necessity, Federated learning (FL) emerges as a relevant artificial intelligence field for developing machine learning (ML) models in a distributed and decentralized environment. FL allows ML models to be trained on local devices without any need for centralized data transfer, thereby reducing both the exposure of sensitive data and the possibility of data interception
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Cybersecurity Landscape on Remote State Estimation: A Comprehensive Review IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Jing Zhou, Jun Shang, Tongwen Chen
Cyber-physical systems (CPSs) have emerged as an essential area of research in the last decade, providing a new paradigm for the integration of computational and physical units in modern control systems. Remote state estimation (RSE) is an indispensable functional module of CPSs. Recently, it has been demonstrated that malicious agents can manipulate data packets transmitted through unreliable channels
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A Weakly-Supervised Crowd Density Estimation Method Based on Two-Stage Linear Feature Calibration IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Yong-Chao Li, Rui-Sheng Jia, Ying-Xiang Hu, Hong-Mei Sun
In a crowd density estimation dataset, the annotation of crowd locations is an extremely laborious task, and they are not taken into the evaluation metrics. In this paper, we aim to reduce the annotation cost of crowd datasets, and propose a crowd density estimation method based on weakly-supervised learning, in the absence of crowd position supervision information, which directly reduces the number
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Side Information-Based Stealthy False Data Injection Attacks Against Multi-Sensor Remote Estimation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Haibin Guo, Zhong-Hua Pang, Chao Li
Dear Editor, This letter investigates a novel stealthy false data injection (FDI) attack scheme based on side information to deteriorate the multi-sensor estimation performance of cyber-physical systems (CPSs). Compared with most existing works depending on the full system knowledge, this attack scheme is only related to attackers' sensor and physical process model. The design principle of the attack
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Goal-Oriented Control Systems (GOCS): From HOW to WHAT IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Wen-Hua Chen
Brief: New control theory is required to underpin safe design and deployment of future highly automated systems to deal with uncertain environments and complicated tasks, enabled by AI and other advanced technologies. Goal-Oriented Control Systems offer potential to transform the control system design from currently instructing a control system how to perform a task to specifying what is to be achieved
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Label Recovery and Trajectory Designable Network for Transfer Fault Diagnosis of Machines With Incorrect Annotation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Bin Yang, Yaguo Lei, Xiang Li, Naipeng Li, Asoke K. Nandi
The success of deep transfer learning in fault diagnosis is attributed to the collection of high-quality labeled data from the source domain. However, in engineering scenarios, achieving such high-quality label annotation is difficult and expensive. The incorrect label annotation produces two negative effects: 1) the complex decision boundary of diagnosis models lowers the generalization performance
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Digital CEOs in Digital Enterprises: Automating, Augmenting, and Parallel in Metaverse/CPSS/TAOs IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Juanjuan Li, Rui Qin, Sangtian Guan, Xiao Xue, Peng Zhu, Fei-Yue Wang
BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies [1]–[3] Their significance stems not only from their exceptional ability to process complex data and simulate advanced cognitive functions, but also from their potential to drive innovation across various industries. When it comes to their value creation, the commercial application is undoubtedly
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Attack-Resilient Distributed Cooperative Control of Virtually Coupled High-Speed Trains via Topology Reconfiguration IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Shunyuan Xiao, Xiaohua Ge, Qing Wu
Dear Editor, This letter addresses the resilient distributed cooperative control problem of a virtually coupled train convoy under stochastic disturbances and cyber attacks. The main purpose is to achieve distributed coordination of virtually coupled high-speed trains with the prescribed inter-train distance and same cruise velocity, while preserving driving security of the train convoy against a class
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Adaptive Sensor-Fault Tolerant Control of Unmanned Underwater Vehicles With Input Saturation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Xuerao Wang, Qingling Wang, Yanxu Su, Yuncheng Ouyang, Changyin Sun
This paper investigates the tracking control problem for unmanned underwater vehicles (UUVs) systems with sensor faults, input saturation, and external disturbance caused by waves and ocean currents. An active sensor fault-tolerant control scheme is proposed. First, the developed method only requires the inertia matrix of the UUV, without other dynamic information, and can handle both additive and
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When Does Sora Show: The Beginning of TAO to Imaginative Intelligence and Scenarios Engineering IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Fei-Yue Wang, Qinghai Miao, Lingxi Li, Qinghua Ni, Xuan Li, Juanjuan Li, Lili Fan, Yonglin Tian, Qing-Long Han
During our discussion at workshops for writing “What Does ChatGPT Say: The DAO from Algorithmic Intelligence to Linguistic Intelligence” [1], we had expected the next milestone for Artificial Intelligence (AI) would be in the direction of Imaginative Intelligence (II), i.e., something similar to automatic words-to-videos generation or intelligent digital movies/theater technology that could be used
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Quantization and Event-Triggered Policy Design for Encrypted Networked Control IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Yongxia Shi, Ehsan Nekouei
This paper proposes a novel event-driven encrypted control framework for linear networked control systems (NCSs), which relies on two modified uniform quantization policies, the Paillier cryptosystem, and an event-triggered strategy. Due to the fact that only integers can work in the Pailler cryptosystem, both the real-valued control gain and system state need to be first quantized before encryption
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Relaxed Stability Criteria for Time-Delay Systems: A Novel Quadratic Function Convex Approximation Approach IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Shenquan Wang, Wenchengyu Ji, Yulian Jiang, Yanzheng Zhu, Jian Sun
This paper develops a quadratic function convex approximation approach to deal with the negative definite problem of the quadratic function induced by stability analysis of linear systems with time-varying delays. By introducing two adjustable parameters and two free variables, a novel convex function greater than or equal to the quadratic function is constructed, regardless of the sign of the coefficient
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Computational Experiments for Complex Social Systems: Experiment Design and Generative Explanation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Xiao Xue, Deyu Zhou, Xiangning Yu, Gang Wang, Juanjuan Li, Xia Xie, Lizhen Cui, Fei-Yue Wang
Powered by advanced information technology, more and more complex systems are exhibiting characteristics of the cyber-physical-social systems (CPSS). In this context, computational experiments method has emerged as a novel approach for the design, analysis, management, control, and integration of CPSS, which can realize the causal analysis of complex systems by means of “algorithmization” of “counterfactuals”
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Data-Based Filters for Non-Gaussian Dynamic Systems with Unknown Output Noise Covariance IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-03-18 Elham Javanfar, Mehdi Rahmani
This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise. The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system. Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering, we first propose
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Parallel Vision ⊇ Image Synthesis/Augmentation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Wenwen Zhang, Wenbo Zheng, Qiang Li, Fei-Yue Wang
Dear Editor, Scene understanding is an essential task in computer vision. The ultimate objective of scene understanding is to instruct computers to understand and reason about the scenes as humans do. Parallel vision is a research framework that unifies the explanation and perception of dynamic and complex scenes. Parallel vision's rationality has been proven through recent research hotspots in artificial
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Sequential Inverse Optimal Control of Discrete-Time Systems IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Sheng Cao, Zhiwei Luo, Changqin Quan
This paper presents a novel sequential inverse optimal control (SIOC) method for discrete-time systems, which calculates the unknown weight vectors of the cost function in real time using the input and output of an optimally controlled discrete-time system. The proposed method overcomes the limitations of previous approaches by eliminating the need for the invertible Jacobian assumption. It calculates
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More Than Lightening: A Self-Supervised Low-Light Image Enhancement Method Capable for Multiple Degradations IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Han Xu, Jiayi Ma, Yixuan Yuan, Hao Zhang, Xin Tian, Xiaojie Guo
Low-light images suffer from low quality due to poor lighting conditions, noise pollution, and improper settings of cameras. To enhance low-light images, most existing methods rely on normal-light images for guidance but the collection of suitable normal-light images is difficult. In contrast, a self-supervised method breaks free from the reliance on normal-light data, resulting in more convenience
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Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Yi Zheng, Yanye Wang, Xun Meng, Shaoyuan Li, Hao Chen
In this paper, distributed model predictive control (DMPC) for island DC micro-grids (MG) with wind/photovoltaic (PV)/battery power is proposed, which coordinates all distributed generations (DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement. Based on the feedback of the bus voltage, the deviation of the current is dispatched
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Dynamic Vision Enabled Contactless Cross-Domain Machine Fault Diagnosis with Neuromorphic Computing IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Xinrui Chen, Xiang Li, Shupeng Yu, Yaguo Lei, Naipeng Li, Bin Yang
Dear Editor, This letter presents a novel dynamic vision enabled contactless cross-domain fault diagnosis method with neuromorphic computing. The event-based camera is adopted to capture the machine vibration states in the perspective of vision. A specially designed bio-inspired deep transfer spiking neural network (SNN) model is proposed for processing the event streams of visionary data, feature
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Dynamic Constraint-Driven Event-Triggered Control of Strict-Feedback Systems Without Max/Min Values on Irregular Constraints IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Zhuwu Shao, Yujuan Wang, Zeqiang Li, Yongduan Song
This work proposes an event-triggered adaptive control approach for a class of uncertain nonlinear systems under irregular constraints. Unlike the constraints considered in most existing papers, here the external irregular constraints are considered and a constraints switching mechanism (CSM) is introduced to circumvent the difficulties arising from irregular output constraints. Based on the CSM, a
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A Dual Closed-Loop Digital Twin Construction Method for Optimizing the Copper Disc Casting Process IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Zhaohui Jiang, Chuan Xu, Jinshi Liu, Weichao Luo, Zhiwen Chen, Weihua Gui
The copper disc casting machine is core equipment for producing copper anode plates in the copper metallurgy industry. The copper disc casting machine casting package motion curve (CPMC) is significant for precise casting and efficient production. However, the lack of exact casting modeling and real-time simulation information severely restricts dynamic CPMC optimization. To this end, a liquid copper
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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems with Application to Power Systems IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Jianguo Zhao, Chunyu Yang, Weinan Gao, Linna Zhou, Xiaomin Liu
This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems (SPSs) with unknown dynamics based on reinforcement learning (RL). Taking into account the slow and fast characteristics among system states, the interconnected SPS is decomposed into the slow time-scale dynamics and the fast time-scale dynamics through singular perturbation
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Set-Membership Filtering Approach to Dynamic Event-Triggered Fault Estimation for a Class of Nonlinear Time-Varying Complex Networks IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Xiaoting Du, Lei Zou, Maiying Zhong
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks, utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism (DETM). In order to optimize communication resource utilization, the DETM is employed to determine whether the current measurement data should be transmitted to the estimator
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A Novel Disturbance Observer Based Fixed-Time Sliding Mode Control for Robotic Manipulators with Global Fast Convergence IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Dan Zhang, Jiabin Hu, Jun Cheng, Zheng-Guang Wu, Huaicheng Yan
This paper proposes a new global fixed-time sliding mode control strategy for the trajectory tracking control of uncertain robotic manipulators. First, a fixed-time disturbance observer (FTDO) is designed to deal with the adverse effects of model uncertainties and external disturbances in the manipulator systems. Then an adaptive scheme is used and the adaptive FTDO (AFTDO) is developed, so that the
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Depth-Guided Vision Transformer With Normalizing Flows for Monocular 3D Object Detection IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Cong Pan, Junran Peng, Zhaoxiang Zhang
Monocular 3D object detection is challenging due to the lack of accurate depth information. Some methods estimate the pixel-wise depth maps from off-the-shelf depth estimators and then use them as an additional input to augment the RGB images. Depth-based methods attempt to convert estimated depth maps to pseudo-LiDAR and then use LiDAR-based object detectors or focus on the perspective of image and
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Value Iteration-Based Cooperative Adaptive Optimal Control for Multi-Player Differential Games With Incomplete Information IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Yun Zhang, Lulu Zhang, Yunze Cai
This paper presents a novel comperative value iteration (VI)-based adaptive dynamic programming method for multi-player differential game models with a convergence proof. The players are divided into two groups in the learning process and adapt their policies sequentially. Our method removes the dependence of admissible initial policies, which is one of the main drawbacks of the PI-based frameworks
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Decentralized Optimal Control and Stabilization of Interconnected Systems with Asymmetric Information IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Na Wang, Xiao Liang, Hongdan Li, Xiao Lu
The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information. Compared with previous work, a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time. The main challenge lies in three aspects: Firstly
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Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Xiongbo Wan, Chaoling Zhang, Fan Wei, Chuan-Ke Zhang, Min Wu
This article focuses on dynamic event-triggered mechanism (DETM)-based model predictive control (MPC) for T-S fuzzy systems. A hybrid dynamic variables-dependent DETM is carefully devised, which includes a multiplicative dynamic variable and an additive dynamic variable. The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem (OP). To facilitate the co-design of the
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A Mean-Field Game for a Forward-Backward Stochastic System with Partial Observation and Common Noise IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Pengyan Huang, Guangchen Wang, Shujun Wang, Hua Xiao
This paper considers a linear-quadratic (LQ) mean-field game governed by a forward-backward stochastic system with partial observation and common noise, where a coupling structure enters state equations, cost functionals and observation equations. Firstly, to reduce the complexity of solving the mean-field game, a limiting control problem is introduced. By virtue of the decomposition approach, an admissible
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A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of $n$-DOF Upper-Limb Exoskeleton With Input Deadzone IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Dingxin He, HaoPing Wang, Yang Tian, Yida Guo
This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for $n$ -DOF upper-limb exoskeleton in presence of uncertainties, external disturbances and input deadzone. Considering the model complexity and input deadzone, a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design. Firstly
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Exponential Synchronization of Delayed Stochastic Complex Dynamical Networks via Hybrid Impulsive Control IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Yao Cui, Pei Cheng, Xiaohua Ge
Dear Editor, This letter addresses the synchronization problem of a class of delayed stochastic complex dynamical networks consisting of multiple drive and response nodes. The aim is to achieve mean square exponential synchronization for the drive-response nodes despite the simultaneous presence of time delays and stochastic noises in node dynamics. Toward this aim, a hybrid impulsive controller, featuring
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Multi-Timescale Distributed Approach to Generalized-Nash-Equilibrium Seeking in Noncooperative Nonconvex Games IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Banghua Huang, Yang Liu, Kit Ian Kou, Weihua Gui
Dear Editor, The distributed generalized-Nash-equilibrium (GNE) seeking in noncooperative games with nonconvexity is the topic of this letter. Inspired by the sequential quadratic programming (SQP) method, a multi-timescale multi-agent system (MAS) is developed, and its convergence to a critical point of the game is proven. To illustrate the qualities and efficacy of the theoretical findings, a numerical
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Simulation Analysis of Deformation Control for Magnetic Soft Medical Robots IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Jingxi Wang, Baoyu Liu, Edmond Q. Wu, Jin Ma, Ping Li
Dear Editor, This letter presents a biocompatible cross-shaped magnetic soft robot and investigates its deformation mode control strategy through COMSOL modeling and simulation. Magnetic soft robots offer novel avenues for precise treatment within intricate regions of the human body. However, the biosafety and precise control characteristics of robots need to be further improved for practical medical
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Communication-Aware Mobile Relaying via an AUV for Minimal Wait Time: A Broad Learning-Based Solution IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Wenqiang Cao, Jing Yan, Xian Yang, Cailian Chen, Xinping Guan
Dear Editor, This letter studies the communication-aware mobile relaying via an autonomous underwater vehicle (AUV) for minimal wait time. Compared with the analysis-based channel prediction solution, the proposed discrete Kirchhoff approximation solution has a higher estimation accuracy. Different with the deep learning (DL), a semi-supervised broad learning system (BLS) based relaying controller
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Achieving 500X Acceleration for Adversarial Robustness Verification of Tree-Based Smart Grid Dynamic Security Assessment IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Chao Ren, Chunran Zou, Zehui Xiong, Han Yu, Zhao-Yang Dong, Niyato Dusit
Dear Editor, This letter presents a novel and efficient adversarial robustness verification method for tree-based smart grid dynamic security assessment (DSA). Based on tree algorithms technique, the data-driven smart grid DSA has received significant research interests in recent years. However, the well-trained tree-based DSA models with high accuracy are always vulnerable caused by some physical
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Dendritic Deep Learning for Medical Segmentation IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Zhipeng Liu, Zhiming Zhang, Zhenvu Lei, Masaaki Omura, Rong-Long Wang, Shangce Gao
Dear Editor, This letter presents a novel segmentation approach that leverages dendritic neurons to tackle the challenges of medical imaging segmentation. In this study, we enhance the segmentation accuracy based on a SegNet variant including an encoder-decoder structure, an upsampling index, and a deep supervision method. Furthermore, we introduce a dendritic neuron-based convolutional block to enable
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Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-02-12 Lin Lin, Jinde Cao, Jianquan Lu, Leszek Rutkowski
Dear Editor, This letter deals with the set stabilization of stochastic Boolean control networks (SBCNs) by the pinning control strategy, which is to realize the full control for systems by imposing control inputs on a fraction of agents. The pinned agents are determined based on the information on the network structure, rather than the whole state transition, of an SBCN. Regarding each pinned agent
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Social Radars: Finding Targets in Cyberspace for Cybersecurity IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Lili Fan, Changxian Zeng, Yutong Wang, Jiaqi Ma, Fei-Yue Wang
Inspired by the insight from American political scientist Lasswell, who summarized the environmental role in societal surveillance [1], Schramm coined the term “social radar” [2] as it resembles the activities of radar in collecting and processing information, playing a crucial role in helping humans perceive changes in the internal and external environment and promptly adjusting adaptive behaviors
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Reinforcement Learning in Process Industries: Review and Perspective IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Oguzhan Dogru, Junyao Xie, Om Prakash, Ranjith Chiplunkar, Jansen Soesanto, Hongtian Chen, Kirubakaran Velswamy, Fadi Ibrahim, Biao Huang
This survey paper provides a review and perspective on intermediate and advanced reinforcement learning (RL) techniques in process industries. It offers a holistic approach by covering all levels of the process control hierarchy. The survey paper presents a comprehensive overview of RL algorithms, including fundamental concepts like Markov decision processes and different approaches to RL, such as
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Advancements in Humanoid Robots: A Comprehensive Review and Future Prospects IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yuchuang Tong, Haotian Liu, Zhengtao Zhang
This paper provides a comprehensive review of the current status, advancements, and future prospects of humanoid robots, highlighting their significance in driving the evolution of next-generation industries. By analyzing various research endeavors and key technologies, encompassing ontology structure, control and decision-making, and perception and interaction, a holistic overview of the current state
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Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yijing Xie, Yichen Zhang, Wei-Jen Lee, Zongli Lin, Yacov A. Shamash
The power grid is undergoing a transformation from synchronous generators (SGs) toward inverter-based resources (IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants (VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically
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Noise-Tolerant ZNN-Based Data-Driven Iterative Learning Control for Discrete Nonaffine Nonlinear MIMO Repetitive Systems IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yunfeng Hu, Chong Zhang, Bo Wang, Jing Zhao, Xun Gong, Jinwu Gao, Hong Chen
Aiming at the tracking problem of a class of discrete nonaffine nonlinear multi-input multi-output (MIMO) repetitive systems subjected to separable and nonseparable disturbances, a novel data-driven iterative learning control (ILC) scheme based on the zeroing neural networks (ZNNs) is proposed. First, the equivalent dynamic linearization data model is obtained by means of dynamic linearization technology
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A Self-Adapting and Efficient Dandelion Algorithm and Its Application to Feature Selection for Credit Card Fraud Detection IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Honghao Zhu, MengChu Zhou, Yu Xie, Aiiad Albeshri
A dandelion algorithm (DA) is a recently developed intelligent optimization algorithm for function optimization problems. Many of its parameters need to be set by experience in DA, which might not be appropriate for all optimization problems. A self-adapting and efficient dandelion algorithm is proposed in this work to lower the number of DA's parameters and simplify DA's structure. Only the normal
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PAPS: Progressive Attention-Based Pan-sharpening IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yanan Jia, Qiming Hu, Renwei Dian, Jiayi Ma, Xiaojie Guo
Pan-sharpening aims to seek high-resolution multi-spectral (HRMS) images from paired multispectral images of low resolution (LRMS) and panchromatic (PAN) images, the key to which is how to maximally integrate spatial and spectral information from PAN and LRMS images. Following the principle of gradual advance, this paper designs a novel network that contains two main logical functions, i.e., detail
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Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yi Yu, Guo-Ping Liu, Yi Huang, Peng Shi
DC-DC converter-based multi-bus DC microgrids (MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the
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Fault Estimation for a Class of Markov Jump Piecewise-Affine Systems: Current Feedback Based Iterative Learning Approach IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Yanzheng Zhu, Nuo Xu, Fen Wu, Xinkai Chen, Donghua Zhou
In this paper, the issues of stochastic stability analysis and fault estimation are investigated for a class of continuous-time Markov jump piecewise-affne (PWA) systems against actuator and sensor faults. Firstly, a novel mode-dependent PWA iterative learning observer with current feedback is designed to estimate the system states and faults, simultaneously, which contains both the previous iteration
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UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Jiawen Kang, Junlong Chen, Minrui Xu, Zehui Xiong, Yutao Jiao, Luchao Han, Dusit Niyato, Yongju Tong, Shengli Xie
Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation, which consumes intensive computing resources
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Equilibrium Strategy of the Pursuit-Evasion Game in Three-Dimensional Space IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Nuo Chen, Linjing Li, Wenji Mao
The pursuit-evasion game models the strategic interaction among players, attracting attention in many realistic scenarios, such as missile guidance, unmanned aerial vehicles, and target defense. Existing studies mainly concentrate on the cooperative pursuit of multiple players in two-dimensional pursuit-evasion games. However, these approaches can hardly be applied to practical situations where players
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Sparse Reconstructive Evidential Clustering for Multi-View Data IEEE/CAA J. Automatica Sinica (IF 11.8) Pub Date : 2024-01-29 Chaoyu Gong, Yang You
Although many multi-view clustering (MVC) algorithms with acceptable performances have been presented, to the best of our knowledge, nearly all of them need to be fed with the correct number of clusters. In addition, these existing algorithms create only the hard and fuzzy partitions for multi-view objects, which are often located in highly-overlapping areas of multi-view feature space. The adoption