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Joint Probabilistic Scheduling and Resource Allocation for Wireless networked control systems

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 258-260页

作者： Meng Zheng Lei Zhang Wei Liang IEEE the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences the University of Chinese Academy of Sciences

Dear Editor,This letter presents a joint probabilistic scheduling and resource allocation method(PSRA) for 5G-based wireless networked control systems(WNCSs). As a control-aware optimization method, PSRA minimizes the linear quadratic Gaussian(LQG) control cost of WNCSs by optimizing the activation probability of subsystems, the number of uplink repetitions, and the durations of uplink and downlink phases. Simulation results show that PSRA achieves smaller LQG control costs than existing works.

关键词： networked control systems

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Soft Resource Slicing for Industrial Mixed Traffic in 5G Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 463-465页

作者： Jingfang Ding Meng Zheng Haibin Yu the State Key Laboratory of Robotics and the Key Laboratory of Networked Control Systems Chinese Academy of Sciences the Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences the University of Chinese Academy of Sciences IEEE

Dear Editor,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-Qo S-aware soft slicing (TQASS) scheme and a resource-efficiency-aware soft slicing (REASS) scheme.

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Robust Output Regulation With Prescribed Performance for Second-Order Non-Polynomial Nonlinear systems

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 14234-14246页

作者： Liu, Wei Luo, Jialei Sun, Weijie South China University of Technology Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education School of Automation Science and Engineering Guangzhou510641 China

This article focuses on the robust output regulation problem with prescribed performance for uncertain second-order nonlinear systems with non-polynomial nonlinearity. According to the existing framework for the robust output regulation problem of such nonlinear systems, we introduce some standard assumptions, and then construct two internal models of nonlinear forms to reproduce the steady-state information. Then, we convert the considered problem into the robust stabilization problem with prescribed performance of an augmented system containing the studied nonlinear system and the internal models. We incorporate a novel error transformation into the existing technique to design a stabilization controller, based on which we synthesize our control law to solve our original problem. Finally, we present two simulation examples to test our results. © 2004-2012 IEEE.

关键词： Nonlinear systems Performance evaluation Regulation Steady-state Transient analysis Polynomials Mathematical models Output feedback Adaptive systems Symmetric matrices

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SkateDuct: Utilizing Vector Thrust of Ducted Fan UAVs for Terrestrial-Aerial Locomotion

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IEEE Robotics and Automation Letters 2025年第6期10卷 6047-6054页

作者： Yin, Zhong Pei, Hailong South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems Guangzhou510641 China

Ducted fan UAVs (DFUAVs), characterized by vector thrust, vertical takeoff and landing (VTOL) capabilities, and high safety, have found widespread applications in both military and civilian scenarios. However, their limited endurance remains a significant constraint on their broader applications. To address this challenge, in this letter we explore a novel approach that exploits the vector thrust capabilities of DFUAVs to enable terrestrial-aerial locomotion through simple modifications without the need for additional actuators. The design of a DFUAV employing passive wheels for continuous ground and aerial operation is presented. This configuration allows for unchanged attitude and static stability during ground movement, with only a 10.3% increase in weight. Fluid simulations were conducted to analyze the variation in control vane aerodynamic efficiency under ground effect, leading to the development of a ground-effect-adjusted aerodynamic model based on experimental data. Furthermore, the dynamics of ground movement are analyzed, and a corresponding controller is developed, establishing a complete framework for seamless transition between terrestrial and aerial modes. Extensive real-world flight experiments validate the proposed structural design and control methods. By utilizing terrestrial locomotion, the UAV's energy consumption is reduced to just 33.9% of that during flight, effectively extending its operational duration by more than ten times. © 2016 IEEE.

关键词： Antenna grounds

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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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A dynamic point cloud fast compression framework based on eliminating spatial and temporal redundancy

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Multimedia Tools and Applications 2025年 1-19页

作者： Su, Kainan Wang, Zunran Yang, Chenguang The Key Laboratory of Autonomous Systems and Networked Control College of Automation Science and Engineering South China University of Technology Guangzhou510641 China Huawei Technologies Co Ltd Shenzhen518028 China

Dynamic point clouds can be compressed by eliminating spatial and temporal redundancy, but few research studies have considered both simultaneously. Existing research can only distinguish the specific foreground and background of the scene, achieving the former with a limited compression ratio, while the latter relies on 3D motion estimation with high computing complexity. Therefore, it is difficult to meet the real-time requirement of building remote human-robot interaction system. Aiming at the shortcomings of the above methods, a dynamic point cloud fast compression framework based on eliminating spatial and temporal redundancy is proposed. On the one hand, for eliminating the spatial redundancy, the information of the recognized objects in point cloud data will be replaced with their categories and poses. On the other hand, we eliminate the temporal redundancy by using the motion vector of the point cloud macroblock. Specifically, in order to reduce cost time of the 3D motion estimation, we firstly introduce the 2D image ORB feature to calculate the motion vector from current frame to key frame, and then look for the similar macroblock in key frame. Thus, the information of the macroblocks similar to the key frame in the current frame is replaced by the index of the corresponding macroblocks of the key frame and the motion vector. Experimental results show that the proposed method has higher computational efficiency and compression quality than the existing compression algorithm. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Semantic Segmentation

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Geometric attitude tracking control of quadrotor UAVs with adaptive extended state observers

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ISA Transactions 2025年 160卷 289-297页

作者： Wang, Liping Chen, Jiapeng Huang, Yuyuan Zhu, Yongbin Pei, Hailong Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong School of Automation Science and Engineering South China University of Technology Guangzhou510640 China

This paper studies a geometric attitude tracking control problem of quadrotor unmanned aerial vehicles (UAVs) with adaptive extended state observers (AESOs). Through coordinate transformation, the error dynamic of AESO can be transformed into a canonical form which is easier to analyze by linear time-varying theory. In the presence of unknown disturbances and system uncertainties, the estimated error and stability of AESO can be analyzed. Simultaneously, a geometric tracking controller is developed on SO(3) with AESOs which guarantees that the error exponentially converges to a bounded set related to the estimated error. Some examples and a flight test are given to verify the availability of the control scheme. © 2025

关键词： Unmanned aerial vehicles (UAV)

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An intelligent matching method for the equivalent circuit of electrochemical impedance spectroscopy based on Random Forest

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材料科学技术（英文版） 2025年第6期209卷 300-310页

作者： Wenbo Chen Bingjun Yan Aidong Xu Xin Mu Xiufang Zhou Maowei Jiang Changgang Wang Rui Li Jie Huang Junhua Dong Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110169China Shenyang Institute of Automation Chinese Academy of SciencesShenyang 110169China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China Shenyang National Laboratory for Materials Science Institute of Metal ResearchChinese Academy of SciencesShenyang 110016China General Research Institute China Oil & Gas Pipeline Network CorporationLangfang 065000China

One of the core works of analyzing Electrochemical Impedance Spectroscopy(EIS)data is to select an appropriate equivalent circuit model to quantify the parameters of the electrochemical reaction ***,this process often relies on human experience and judgment,which will introduce subjectivity and *** this paper,an intelligent approach is proposed for matching EIS data to their equivalent circuits based on the Random Forest *** can automatically select the most suitable equivalent circuit model based on the characteristics and patterns of EIS *** the typical scenario of metal corrosion,an atmospheric corrosion EIS dataset of low-carbon steel is constructed in this paper,which includes five different corrosion *** dataset was used to validate and evaluate the pro-posed method in this *** contributions of this paper can be summarized in three aspects:(1)This paper proposes a method for selecting equivalent circuit models for EIS data based on the Random Forest algorithm.(2)Using authentic EIS data collected from metal atmospheric corrosion,the paper es-tablishes a dataset encompassing five categories of metal corrosion scenarios.(3)The superiority of the proposed method is validated through the utilization of the established authentic EIS *** ex-periment results demonstrate that,in terms of equivalent circuit matching,this method surpasses other machine learning algorithms in both precision and ***,it shows strong applicability in the analysis of EIS data.

关键词： Electrochemical impedance spectroscopy Random forest Corrosion Equivalent circuit model

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Enhancing Robot Learning Through Cognitive Reasoning Trajectory Optimization Under Unknown Dynamics

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IEEE Robotics and Automation Letters 2025年第6期10卷 5401-5408页

作者： Dong, Qingwei Wu, Tingting Zeng, Peng Zang, Chuanzhi Wan, Guangxi Cui, Shijie Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China China Mobile Research Institute Beijing100053 China Shenyang University of Technology School of Artifcial Intelligence Shenyang110870 China

In the domain of robot learning, equipping robots with the capability to swiftly acquire operational skills poses a significant challenge. Currently, reinforcement learning techniques are adept at addressing dynamic, unstructured problems involving rich contact scenarios. However, the convergence rate of these algorithms is often slow due to the high dimensionality of the robot state-action mapping space and the extensive initial policy search space. Meanwhile, advancements in large language models (LLMs) have endowed these models with a degree of logical reasoning ability, enabling them to take goal-oriented actions proactively during the initial phase of a robotic task. These models can implicitly generate features of states and uncover underlying patterns in trajectory generation. Yet, in complex manipulative tasks involving rich contact scenarios, LLMs still fall short. Thus, integrating the robust interactive capabilities of reinforcement learning with the strong logical reasoning of LLMs, and enhancing policy search with LLMs, could potentially accelerate the speed of policy searches significantly. In this letter, we introduce a Cognitive Reasoning Trajectory Optimization method. This approach utilizes Low-level Cognitive control Tuning to enable LLMs with robust logical reasoning to make effective single-step decisions in Markov Decision Process (MDP) tasks. By fitting dynamic models with high-quality cognitive reasoning data and optimizing control strategies, this method constrains the policy search space and enhances the efficiency of trajectory optimization. Experimental results on various manipulative tasks using the Sawyer robot in the Mujoco simulator validate the effectiveness of the proposed algorithm. © 2016 IEEE.

关键词： Markov processes

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Distributed Adaptive Tracking control for Fuzzy Nonlinear MASs Under Round-Robin Protocol

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IEEE Transactions on Fuzzy systems 2025年第5期33卷 1488-1498页

作者： Fan, Sha Meng, Min Fu, Yukai Deng, Chao Nanjing University of Posts and Telecommunications College of Automation College of Artificial Intelligence Nanjing210023 China Tongji University Department of Control Science and Engineering College of Electronics and Information Engineering Shanghai200070 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang110016 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing210049 China

In this article, the cooperative fuzzy tracking control problem for a type of high-order nonlinear multi-agent systems under the Round-Robin (RR) communication protocol is solved. To effectively reduce the communication among agents, an RR communication protocol is first proposed, where each agent can communicate with only one neighbor at any given time. Based on the developed communication protocol, a hierarchical control approach is introduced, consisting of a distributed observer layer that utilizes information from both local and neighboring agents, and a decentralized control layer that operates solely based on local agent information. Specifically, a distributed observer is designed in the distributed observer layer to achieve the distributed observation objective by introducing a time-varying gain in the observer input. Furthermore, an improved distributed observer with the upper triangular form is constructed to produce a signal with high-order derivatives. In the decentralized control layer, fuzzy adaptive controllers are designed for all agents by using the backstepping technique. By using the Lyapunov stability theory, rigorous stability analysis shows that the cooperative fuzzy tracking control problem is solved under the developed hierarchical control approach. In the end, a simulation example is presented to demonstrate the validity of our proposed method. © 1993-2012 IEEE.

关键词： Protocols Observers Stability analysis Decentralized control Backstepping Vectors Symmetric matrices Network topology Telecommunications System dynamics

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