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Neural-based prescribed-time consensus control for multiagent systems via dynamic memory event-triggered mechanism

Science China(Technological Sciences) 2025年第3期68卷 217-227页

作者： Xiaohong ZHENG Hui MA Qi ZHOU Hongyi LI School of Automation Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Controland Guangdong Provincial Key Laboratory for Intelligent Decision and Cooperative ControlGuangdong University of TechnologyGuangzhou510006China School of Mathematics and Statistics Guangdong University of TechnologyGuangzhou510006China College of Electronic and Information Engineering and the Chongqing Key Laboratory of Generic Technology and System of Service Robots Southwest UniversityChongqing400715China

This work investigates the implementation of distributed prescribed-time neural network(NN)control for nonlinear multiagent systems(MASs)using a dynamic memory event-triggered mechanism(DMETM).First,it introduces a composite learning technique in NN *** method leverages the prediction error within the NN update law to enhance the accuracy of the unknown nonlinearity ***,by introducing a time-varying transformation,the study establishes a distributed prescribed-time control *** notable feature of this algorithm is its ability to predetermine the convergence time independently of initial conditions or control ***,the DMETM is established to reduce the actuation frequency of the *** the conventional memoryless dynamic event-triggered mechanism,the DMETM incorporates a memory term to further increase triggering *** a distributed estimator for the leader,the DMETM-based NN prescribed-time controller is designed in a fully distributed manner,which guarantees that all signals in the closed-loop system remain bounded within the prescribed ***,simulation results are presented to validate the effectiveness of the proposed algorithm.

关键词： consensus control composite learning control dynamic memory event-triggered control prescribed-time control multiagent systems(MASs)

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Conditional Diffusion Model for Skeleton-based Gesture Recognition with Severe Occlusions

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IEEE Signal Processing Letters 2025年 32卷 1970-1974页

作者： Liu, Jinting Gan, Minggang Du, Yao Guan, keyi Guo, Jia Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing China

In the field of skeleton-based gesture recognition, occlusion remains a significant challenge, significantly degrading performance when key joints are occluded or disturbed. To tackle this issue, we propose DiffTrans, a practical conditional diffusion model for occlusion recognition, which enables skeleton-based gesture recognition under high occlusion by generating more likely samples. This study addresses the hand skeleton occlusion problem by framing it as a conditional denoising problem, where unoccluded data serve as observations and occluded data as repair targets. We employ a conditional diffusion model to impute the missing skeleton data and the DSTANet model, which is based on the transformer, to learn the skeleton feature representations. Research results show that the DiffTrans outperforms existing methods under various occlusion modes, maintaining high performance even in scenarios with a high missing rate. © 1994-2012 IEEE.

关键词： Musculoskeletal system

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Model and Simulation of Multipath Error in DLL for GPS Receiver

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Chinese Journal of Electronics 2025年第3期23卷 508-515页

作者： Lan Cheng Jie Chen Gang Xie Taiyuan University of Technology Taiyuan China Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Although different multipath error models of Delay lock loop (DLL) used in GPS receiver are established, they have never been put together for comparison. Furthermore, no universal simulation method is developed to get a fair comparison among these models. A new model with implicate expression is hence proposed for the coherent DLL and the noncoherent Dot-product (DOT) power mode DLL. Meanwhile, a new simulation method based on the anonymous function in Matlab, which is especially suitable for models with implicit expression, is also proposed to compare the new model with the existing ones. The theoretical analysis and simulation results show that the existing models are the special case of the proposed one. The new simulation method can be used for the comparison of different multipath error models and the multipath error analysis of other DLLs for which only the implicit model is available.

关键词： Analytical models Tracking loops Codes Error analysis Simulation Receivers US Department of Transportation Mathematical models MATLAB Global Positioning system

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Turbulent drag reduction by sector-shaped counter-flow dielectric barrier discharge plasma actuator

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Chinese Physics B 2025年第2期34卷 362-370页

作者： Borui Zheng Shaojie Qi Minghao Yu Jianbo Zhang Linwu Wang Dongliang Bian School of Automation and Information Engineering Xi’an University of TechnologyXi’an 710048China School of Mechanical and Precision Instrument Engineering Xi’an University of TechnologyXi’an 710048China Science and Technology on Plasma Dynamics Laboratory Air Force Engineering UniversityXi’an 710038China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an 710048China Shaanxi University Key Laboratory of Photonic Power Devices and Discharge Regulation Xi’an 710048China

The primary objective in aircraft transportation is to minimize turbulent drag, thereby conserving energy and reducing emissions. We propose a sector-shaped counter-flow dielectric barrier discharge plasma actuator, which leverages jet synthesis for drag reduction. A drag control experiment was conducted in a low-speed wind tunnel with a controlled flow velocity of 9.6 m/s(Re = 1.445 × 10^(4)). This study investigated the effects of varying pulse frequencies and actuation voltages on the turbulent boundary layer. Using a hot-wire measurement system, we analyzed the pulsating and time-averaged velocity distributions within the boundary layer to evaluate the streamwise turbulent drag reduction. The results show that the local TDR decreases as the pulse frequency increases, reaching a maximum reduction of approximately 20.97% at a pulse frequency of 50 Hz. In addition, as the actuation voltage increases, the friction coefficient decreases, increasing the drag reduction rate. The maximum drag reduction of approximately 33.34% is achieved at an actuation voltage of 10 kV.

关键词： plasma flow control turbulent boundary layer turbulent drag reduction

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Multi-agent reinforcement learning system framework based on topological networks in Fourier space

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Applied Soft Computing 2025年 174卷

作者： Sun, Licheng Ding, Ao Ma, Hongbin School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing100081 China

Currently, multi-agent reinforcement learning (MARL) has been applied to various domains such as communications, network management, power systems, and autonomous driving, showcasing broad application scenarios and significant research potential. However, in complex decision-making environments, agents that rely solely on temporal value functions often struggle to capture and extract hidden features and dependencies within long sequences in multi-agent settings. Each agent's decisions are influenced by a sequence of prior states and actions, leading to complex spatiotemporal dependencies that are challenging to analyze directly in the time domain. Addressing these challenges requires a paradigm shift to analyze such dependencies from a novel perspective. To this end, we propose a Multi-Agent Reinforcement Learning system framework based on Fourier Topological Space from the foundational level. This method involves transforming each agent's value function into the frequency domain for analysis. Additionally, we design a lightweight weight calculation method based on historical topological relationships in the Fourier topological space. This addresses issues of instability and poor reproducibility in attention weights, along with various other interpretability challenges. The effectiveness of this method is validated through experiments in complex environments such as the StarCraft Multi-Agent Challenge (SMAC) and Google Football. Furthermore, in the Non-monotonic Matrix Game, our method successfully overcame the limitations of non-monotonicity, further proving its wide applicability and superiority. On the application level, the proposed algorithm is also applicable to various multi-agent system domains, such as robotics and factory robotic arm control. The algorithm can control each joint in a coordinated manner to accomplish tasks such as enabling a robot to stand upright or controlling the movements of robotic arms. © 2025 Elsevier B.V.

关键词： Deep reinforcement learning

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Influence Enhanced Sparse Coordination Graphs for Multi-Agent Reinforcement Learning

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Neural Networks 2025年 188卷 107454页

作者： Zhang, Xiwen Chen, Jie Gan, Ming-Gang Chen, Haoxiang State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

In contemporary Multi-Agent Reinforcement Learning (MARL), effectively enhancing the expressive capacity of value functions has been a persistent research focus. Many studies have employed value decomposition methods;however, due to the neglect of inter-agent collaboration, these methods fall short of achieving optimal performance. Subsequent research introduced coordination graphs into value decomposition methods;nevertheless, these approaches often rely on simplistic rules to evaluate inter-agent collaboration and fail to adequately describe the collaborative relationships of agents in complex environments. Consequently, we propose Influence Enhanced Sparse Coordination Graphs (IESCG) as a solution to provide insights into the aforementioned problem. In this study, we propose influence networks as quantitative descriptions of the importance of collaboration among agents, utilizing them as crucial basis for constructing the topology of Sparse Time-Varying Coordination Graphs. Additionally, we propose Recurrent Payoff Function Networks (RPFN) to incorporate temporal information while providing necessary input to influence networks. Furthermore, Sparse Graph Advantage Selection Coefficients (SGASC) are introduced to stabilize the overall value function across different time steps, ensuring training stability. Experimental investigations conducted on the StarCraft II micromanagement and MACO benchmark indicate that our algorithm not only accelerates convergence and improves winning probabilities but also exhibits more pronounced advantages in complex scenarios. © 2025

关键词： Markov processes

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Finite-Time Consensus of Second-Order Multiagent systems With Input Saturation via Hybrid Sliding-Mode control

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 14623-14632页

作者： Jiang, Xiaowei Jiao, Ranran Li, Bo Zhang, Xianhe Yan, Huaicheng China University of Geosciences School of Automation Wuhan430079 China Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation of Complex Systems Engineering Research Center of Intelligent Geodetection Technology Wuhan430074 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China Anhui University of Finance and Economics School of Finance Bengbu233030 China Hubei Normal University School of Electrical Engineering and Automation Huangshi435002 China Ministry of Education East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China

This paper addresses the finite-time consensus (FTC) issue for second-order multi-agent systems (MASs) with nonlinear disturbances. To tackle the challenges posed by increasingly complex communication environments, an innovative integral sliding-mode surface is designed using event-triggered control. Furthermore, the study explores communication constraints between the leader and followers, employing impulsive control to facilitate communication only at specific intervals. A novel hybrid integral sliding-mode control protocol is advanced for the second-order MASs, which effectively eliminates the "Zeno phenomenon" and notably reduces both communication frequency and energy consumption, thereby enhancing overall communication efficiency. Ultimately, the efficacy of the put forward protocol is verified through simulation examples including comparison experiment. © 2004-2012 IEEE.

关键词： Protocols Sliding mode control Event detection Multi-agent systems Costs Training Topology Switches Sufficient conditions Stability analysis

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Six-Degree-of-Freedom intelligent control of Hypersonic Flight Vehicle

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： An, Hao Wang, Yiming Zhong, Xinyu Ye, Yongfeng Harbin Institute of Technology Space Control and Inertial Technology Research Center National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin China

The six-degree-of-freedom control of hypersonic flight vehicle (HFV) faces great challenges due to complex aerodynamics, inherent couplings and multiple constraints. This paper investigates the six-degree-of-freedom guidance and attitude control problem for unpowered gliding HFV. The guidance loop is based on the predictor-corrector method with three improvements of intelligent prediction acceleration, path constraints accommodation and no-fly zones circumvention. To quickly respond to guidance commands, three attitude channels (i.e., roll, pitch and yaw) are completely decoupled by nonlinear dynamic inverse, based on which a high-performance low-complexity attitude controller is proposed. This benefits from the appropriate integration of barrier function and sliding mode control, while design conditions of three alternative performances (i.e., asymptotic, exponential and preset-time convergences) are discussed. Servo dynamics and physical constraints of aerodynamic control surfaces are also well handled. © 2025 IEEE.

关键词： Hypersonic vehicles

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Target extraction based on hybrid domain features of array GM-APD lidar 10

Target extraction based on hybrid domain features of array G...

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10th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Zhang, Xin Li, Sining Sun, Jianfeng Jiang, Peng Jin, Haowei National Key Laboratory of Laser Spatial Information Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Henan Zhengzhou450000 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

This study proposes a target extraction algorithm for array GM-APD lidar based on hybrid domain features, designed to address the challenges of accurately extracting target region based on the image in complex scenes and high noise interference. We extracted the temporal features of the echo signals and transformed the echo signals into the image domain to enhance the information content and further extract image features. By integrating multi-view K-means clustering and AdaBoost classification methods, we introduced a dynamic weight adjustment mechanism and a region adjustment method based on a correlation coefficient to achieve pixel-type discrimination and target region extraction. Experimental results demonstrate that the proposed method exhibits good robustness and adaptability in complex detection environments. Under conditions of different occlusion, different signal-to-noise ratios, and different target reflectivity, the proposed algorithm significantly outperforms traditional region-growing segmentation methods in terms of accuracy of target region extraction. © 2025 SPIE.

关键词： K-means clustering

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Fully Distributed Output Regulation of Linear Discrete-Time Multi-Agent systems With Markov Switching Topology

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IEEE Transactions on Circuits and systems I: Regular Papers 2025年 1-9页

作者： Liu, Jiamin Li, Zhao-Yan Zhou, Bin Jimei University School of Science Xiamen 361021 China Harbin Institute of Technology School of Mathematics Harbin 150001 China Zhengzhou Research Institute of HIT Zhengzhou 450000 China Harbin Institute of Technology Center for Control Theory and Guidance Technology Harbin 150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin 150001 China

This paper studies the stochastic cooperative output regulation problem for linear discrete-time multi-agent systems (MASs) with Markov switching topologies and communication/input delays. First, a moment stability criterion for an interconnected time-homogeneous Markov jump linear systems is builded. Then, based on the moment stability criterion, a fully distributed output regulation protocol is designed to solve the stochastic cooperative output regulation problem successively. Finally, a numerical simulation is provided to validate the efficiency of the designed protocol. © 2004-2012 IEEE.

关键词： cooperative output regulation discrete-time systems Markov switching topology Multi-agent system time delay

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