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Resilient time-varying formation optimal tracking for heterogeneous multi-agent systems with coupled constraints

IEEE Transactions on automation Science and engineering 2025年 22卷 15274-15285页

作者： Su, Lingfei Lin, Zhi Hua, Yongzhao Shi, Zhexin Dong, Xiwang Lu, Jinhu Wang, Danwei Beihang University School of Artificial Intelligence Institute of Artificial Intelligence Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Shenyuan Honors College Beijing100191 China Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Zhongguancun Laboratory Beijing100094 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore

Formation constrained optimal tracking problems for heterogeneous multi-agent systems under Byzantine attacks are studied. The objective of the honest agents, unaffected by Byzantine attacks, is to find optimal trajectories that minimize the cumulative local cost functions of all honest agents, while simultaneously satisfying the cumulative local inequality constraints and maintaining the formation configuration. A distributed resilient formation tracking controller utilizing preview control and primal-dual strategy is proposed without requiring each agent to know which agents are affected by Byzantine attacks. The performance of the proposed algorithm is analyzed in terms of the upper bounds of dynamic regret and constraint violations. Numerical simulations and experiments, involving one unmanned aerial vehicle and four unmanned ground vehicles, are performed to verify the effectiveness of the obtained results. © 2004-2012 IEEE.

关键词： Cost functions

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Multi-User Cooperative Receive Scheme for Air-to-Ground Vortex Wave Communications

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China Communications 2025年第3期22卷 76-85页

作者： Zhang Beibei Chen Ruirui Lin Jinyang Li Qi Liang Liping Sun Yanjing School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China Jiangsu Automation Research Institute Lianyungang 222061China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an 710071China

Orbital angular momentum(OAM)can achieve multifold increase of spectrum efficiency,but the hollow divergence characteristic and Line-of-Sight(LoS)path requirement impose the crucial challenges for vortex wave *** air-to-ground vortex wave communications,where there exists the LoS path,this paper proposes a multi-user cooperative receive(MUCR)scheme to break through the communication distance limitation caused by the characteristic of vortex wave hollow *** particular,we derive the optimal radial position corresponding to the maximum intensity,which is used to adjust the waist *** on the waist radius and energy ring,the cooperative ground users having the minimum angular square difference are ***,the signal compensation scheme is proposed to decompose OAM signals in air-to-ground vortex wave *** results are presented to verify the superiority of our proposed MUCR scheme.

关键词： air-to-ground capacity cooperative receive multi-user vortex wave communications

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Unformer: A Transformer-Based Approach for Adaptive Multiscale Feature Aggregation in Underwater Image Enhancement

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第4期6卷 1024-1037页

作者： Qing, Yuhao Wang, Yueying Yan, Huaicheng Xie, Xiangpeng Wu, Zhengguang Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China East China University of Science and Technology School of Information Science and Engineering Shanghai200237 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing210023 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China

Underwater imaging is often compromised by light scattering and absorption, resulting in image degradation and distortion. This manifests as blurred details, color shifts, and diminished illumination and contrast, thereby hindering advancements in underwater research. To mitigate these issues, we propose Unformer, an innovative underwater image enhancement (UIE) technique that leverages a transformer-based architecture for multiscale adaptive feature aggregation. Our approach employs a multiscale feature fusion strategy that adaptively restores illumination and detail features. We reevaluate the relationship between convolution and transformer to develop a novel encoder structure. This structure effectively integrates both long-range and short-range dependencies, dynamically combines local and global features, and constructs a comprehensive global context. Furthermore, we propose a unique multibranch decoder architecture that enhances and efficiently extracts spatial context information through the transformer module. Extensive experiments on three datasets demonstrate that our proposed method outperforms other techniques in both subjective and objective evaluations. Compared with the latest methods, Unformer has improved the peak signal-to-noise ratio (PSNR) by 19.5% and 14.8% respectively on the LSUI and EUVP datasets. The code is available at: https://***/yhflq/Unformer. © 2024 IEEE.

关键词： Light scattering

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Building intelligence identification system via large language model watermarking: a survey and beyond

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Artificial Intelligence Review 2025年第8期58卷 1-58页

作者： Wang, Xuhong Jiang, Haoyu Yu, Yi Yu, Jingru Lin, Yilun Yi, Ping Wang, Yingchun Qiao, Yu Li, Li Wang, Fei-Yue Shanghai Artificial Intelligence Laboratory Shanghai200433 China School of Cyber Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Automation BNRist Tsinghua University Beijing100084 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Large Language Models (LLMs) are increasingly integrated into diverse industries, posing substantial security risks due to unauthorized replication and misuse. To mitigate these concerns, robust identification mechanisms are widely acknowledged as an effective strategy. Identification systems for LLMs now rely heavily on watermarking technology to manage and protect intellectual property and ensure data security. However, previous studies have primarily concentrated on the basic principles of algorithms and lacked a comprehensive analysis of watermarking theory and practice from the perspective of intelligent identification. To bridge this gap, firstly, we explore how a robust identity recognition system can be effectively implemented and managed within LLMs by various participants using watermarking technology. Secondly, we propose a mathematical framework based on mutual information theory, which systematizes the identification process to achieve more precise and customized watermarking. Additionally, we present a comprehensive evaluation of performance metrics for LLM watermarking, reflecting participant preferences and advancing discussions on its identification applications. Lastly, we outline the existing challenges in current watermarking technologies and theoretical frameworks, and provide directional guidance to address these challenges. Our systematic classification and detailed exposition aim to enhance the comparison and evaluation of various methods, fostering further research and development toward a transparent, secure, and equitable LLM ecosystem. © The Author(s) 2025.

关键词： Natural language processing systems

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Noncollocated Output Feedback control for the Semilinear Parabolic PDEs Under Input and Output Quantization

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IEEE Transactions on Automatic control 2025年第5期70卷 2934-2947页

作者： Zhao, Xuena Liu, Zhijie Zhang, Shuang Liu, Yu He, Wei University of Science and Technology Beijing Institute of Artificial Intelligence Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Beijing100083 China School of Automation Science and Engineering Engineering Research Center of Precision Electronic Manufacturing Equipment of Ministry of Education Guangzhou510640 China Institute of Artificial Intelligence Key Laboratory of Perception and Control of Intelligent Bionic Unmanned Systems Ministry of Education School of Intelligence Science and Technology Beijing100083 China School of Automation Beijing102206 China

In the context of increasingly networked control systems, this article concentrates on the noncollocated control issue of input and output quantization for industrial processes governed by semilinear parabolic partial differential equation (PDE) systems. Both the control and measurement signals are quantized and transmitted through the network, which causes signal errors and reduces the stability and robustness of the system. A Luenberger-type PDE observer is developed to overcome the control difficulty of quantized measurement feedback signals and noncollocated pointwise sensors. Based on the observed value, a feedback controller is proposed, which undergoes quantization and operates on the distributed actuators within the domain. By employing the Lyapunov direct method, it is demonstrated that the observer can accurately track the system state with exponential precision, and the closed-loop system is exponentially converged. The well-posedness analysis of the closed-loop system is discussed via the C0-semigroup method. The performance of the developed control strategy is validated through simulation examples. © 1963-2012 IEEE.

关键词： Feedback control

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MATD3-Based End-Edge Collaborative Resource Optimization for NOMA-Assisted Industrial Wireless Networks

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Computers, Materials & Continua 2025年第2期82卷 3203-3222页

作者： Ru Hao Chi Xu Jing Liu College of Information Engineering Shenyang University of Chemical TechnologyShenyang110142China State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang110016China

Non-orthogonal multiple access (NOMA) technology has recently been widely integrated into multi-access edge computing (MEC) to support task offloading in industrial wireless networks (IWNs) with limited radio resources. This paper minimizes the system overhead regarding task processing delay and energy consumption for the IWN with hybrid NOMA and orthogonal multiple access (OMA) schemes. Specifically, we formulate the system overhead minimization (SOM) problem by considering the limited computation and communication resources and NOMA efficiency. To solve the complex mixed-integer nonconvex problem, we combine the multi-agent twin delayed deep deterministic policy gradient (MATD3) and convex optimization, namely MATD3-CO, for iterative optimization. Specifically, we first decouple SOM into two sub-problems, i.e., joint sub-channel allocation and task offloading sub-problem, and computation resource allocation sub-problem. Then, we propose MATD3 to optimize the sub-channel allocation and task offloading ratio, and employ the convex optimization to allocate the computation resource with a closed-form expression derived by the Karush-Kuhn-Tucker (KKT) conditions. The solution is obtained by iteratively solving these two sub-problems. The experimental results indicate that the MATD3-CO scheme, when compared to the benchmark schemes, significantly decreases system overhead with respect to both delay and energy consumption.

关键词： Industrial wireless networks(IWNs) multi-access edge computing(MEC) non-orthogonal multiple access(NOMA) task offloading resource allocation

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Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

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IEEE Robotics and automation Letters 2025年第6期10卷 6456-6463页

作者： Sun, Ning Wang, Zelong Cheng, Long Li, Houcheng Niu, Ben Sun, Xijin Li, Ke Shandong Normal University School of Information Science and Engineering Jinan China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Shandong University Institute of Intelligent Medical Engineering School of Control Science and Engineering Jinan China

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while providing sufficient assistance torque is still a challenge. This paper develops a series-parallel self-aligning index finger exoskeleton to assist the index finger in flexion/extension and adduction/abduction training. A series-parallel mechanism driven by two motors simultaneously was proposed for the metacarpophalangeal (MCP) joint, which can ensure human-robot joint axes self-alignment and increase the joint assistance torque. A kinematic compatibility analysis method was proposed, and the kinematic compatibility of the series-parallel mechanism was analyzed. The degrees of freedom and forward kinematics of the proposed mechanism were analyzed, and its workspace was calculated, which results show that the motion range of the MCP joint can meet the grasping training requirements. Preliminary experiments were carried out, and the results indicate that the motion trajectory coefficients of the marker points at the MCP, PIP, and DIP joints averaged for all subjects with and without the proposed exoskeleton are 0.993, 0.956, and 0.939, respectively, which can verify the kinematic transparency of the proposed mechanism. The assistance torque generated by the proposed mechanism on the MCP joint can meet the joint assistance torque requirements. In a word, the proposed exoskeleton can achieve flexion/extension and adduction/abduction training, human-robot joint axes self-alignment, and provide sufficient assistance torque. © 2016 IEEE.

关键词： Exoskeleton (Robotics)

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Data-driven finite-time adaptive attitude tracking control for spacecraft

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Advances in Space Research 2025年第12期75卷 8780-8791页

作者： Wang, Jianhui He, Guangping Bian, Guibin Geng, Shixiong College of Mechanical & Energy Engineering Beijing University Of Technology Beijing100124 China Department of Mechanical and Electrical Engineering North China University of Technology Beijing100144 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

This paper proposes a novel data-driven finite-time adaptive control method for the spacecraft attitude tracking control problem with inertial uncertainty. Based on the dynamic regression extension technique, the disturbance unit matrix is introduced, and the parameter estimation law in the form of algebraic equations is presented, which realizes the arbitrarily small convergence of parameter estimation error. The convergence of parameter estimation errors is verified through stability analysis. Globally non-singular fast terminal sliding mode control is designed to achieve finite-time arrival of the sliding surface and convergence of the system state error. The stability analysis of the closed-loop system demonstrates the effectiveness of the proposed method. Furthermore, the effectiveness and superiority of the proposed method are verified through numerical simulations of spacecraft attitude tracking control. © 2025 COSPAR

关键词： Attitude control

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Brain-Conditional Multimodal Synthesis: A Survey and Taxonomy

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2025年第5期6卷 1080-1099页

作者： Mai, Weijian Zhang, Jian Fang, Pengfei Zhang, Zhijun South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Southeast University School of Computer Science and Engineering Nanjing210096 China South China University of Technology Key Library of Autonomous Systems and Network Control Ministry of Education The School of Automation Science and Engineering Guangzhou510640 China Institute for Super Robotics Huangpu Guangzhou510555 China Nanchang University Jiangxi Thousand Talents Plan Nanchang330031 China Jishou University College of Computer Science and Engineering Jishou416000 China Guangdong Artificial Intelligence and Digital Economy Laboratory Pazhou Lab Guangzhou510335 China Shaanxi University of Technology Shaanxi Provincial Key Laboratory of Industrial Automation School of Mechanical Engineering Hanzhong723001 China Changsha Normal University School of Information Science and Engineering Changsha410100 China Guangdong University of Petrochemical Technology School of Automation Science and Engineering Institute of Artificial Intelligence and Automation Maoming525000 China

In the era of artificial intelligence generated content (AIGC), conditional multimodal synthesis technologies (e.g., text-to-image) are dynamically reshaping the natural content. Brain signals, serving as potential reflections of how the brain interprets external information, exhibit a distinctive one-to-many correspondence with various external modalities. This correspondence makes brain signals emerge as a promising guiding condition for multimodal synthesis (e.g., image, text, and audio), which is crucial for developing practical brain–computer interface systems and unraveling complex mechanisms underlying human perception. This survey comprehensively examines the emerging field of brain-conditional multimodal synthesis, termed AIGC-brain, to delineate the current landscape and future directions. To begin, related neuroimaging datasets and generative models are introduced as the foundation of AIGC-brain decoding and analysis. Next, we present a comprehensive taxonomy according to AIGC-brain methodologies, followed by task-specific representative work and implementation details to facilitate in-depth comparison and analysis. Quality assessments are then introduced for both qualitative and quantitative evaluation. Finally, this survey explores insights gained, outlining current challenges and prospects of AIGC-brain. As a pioneering survey, this article paves the way for future advances in AIGC-brain research. © 2020 IEEE.

关键词： Taxonomies

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Energy-based Swing-up control of the Soft Inverted Pendulum with Affine Curvature

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Nonlinear Dynamics 2025年 1-20页

作者： Wang, Yongjia Xin, Xin School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Institute of Intelligent Unmanned Systems Southeast University Nanjing210096 China

This paper studies the energy-based swing-up control of an underactuated soft inverted pendulum, a template model of soft robots with its base attached to the ground and its curvature described by an affine function. First, this paper presents a necessary and sufficient condition for the linear controllability of the robot around its upright equilibrium point (UEP). Next, without any constraint on its stiffness, this paper derives an energy-based controller to swing up the robot to its UEP, where the pendulum is in its upright position, and provides a necessary and sufficient condition such that the controller is free of singular points. Then, this paper characterizes the patterns of closed-loop equilibrium points with respect to the physical parameters of the pendulum and the gains of the derived controller, and analyzes the closed-loop motion corresponding to the special case in which desired convergence of the total mechanical energy is achieved. In such case, this paper reveals that the UEP is generically the unique closed-loop equilibrium point, and provides clarification regarding its stability. These results serve as guidelines of the design of soft robots and the tuning of control gains to achieve the desired performance of the swing-up control. Finally, this paper conducts numerical simulations to validate the theoretical results and to demonstrate the effectiveness and performance of the derived controller in swinging up the robot to its UEP from initial states far from the UEP, even under the challenging condition of very low stiffness. © The Author(s), under exclusive licence to Springer Nature B.V. 2025.

关键词： Affine transforms

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