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On fast queue consensus of discrete-time second-order multi-agent networks over directed topologies

INFORMATION SCIENCES 2023年第1期636卷

作者： Dai, Jiahao Yi, Jing-Wen Chai, Li Wuhan Univ Sci & Technol Engn Res Ctr Met Automation & Measurement Technol Wuhan 430081 Peoples R China Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

Queue consensus, which aims to drive a set of agents to form a prescribed queue while moving with a common reference velocity, has attracted much attention due to its wide applications. This paper investigates the problem of fast queue consensus for a class of directed multi-agent networks with discrete-time second-order agent dynamics. First, a discrete-time consensus-based control protocol is constructed, and the necessary and sufficient condition to achieve queue consensus is presented. Then, the explicit formulas for the control parameters to achieve the fastest convergence are derived. It is found that the convergence rate of the reference velocity dominates the convergence performance of the overall network. To further accelerate the convergence rate, the agents' node memory is introduced to redesign the update rule of the reference velocity. Furthermore, the analytic formulas of the improved optimal convergence rate and control parameters are established. Finally, numerical examples are given to validate the effectiveness of the proposed theoretical results.

关键词： Queue consensus Multi-agent networks Second-order dynamics Convergence rate

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Accelerated durability evaluation of automotive components under multi-channel random loading

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2024年第5期238卷 1044-1056页

作者： Zhou, Yifu Li, He Northeastern Univ Sch Mech Engn & Automation Shenyang Peoples R China Northeastern Univ Key Lab Vibrat & Control Aerosp Power Equipment Minist Educ Shenyang Peoples R China Northeastern Univ Sch Mech Engn & Automation Lane 3 11Wenhua RdHeping Dist Shenyang 110819 Peoples R China

Accelerated durability evaluation aims to quantify the fatigue damage of automotive components in a shorter time. The quality of accelerated editing directly affects the evaluation's efficiency and accuracy. In this paper, an index-controlled accelerated spectrum editing method is proposed, and the equivalent fatigue damage model of the component is derived. Taking an automotive steering knuckle as the verification object, the proposed accelerated editing method is evaluated from multiple perspectives. The evaluation results show that the proposed method has apparent advantages in compression efficiency, damage consistency, and retaining the frequency domain impact on the component.

关键词： Fatigue damage durability evaluation accelerated editing steering knuckle damage consistency

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A learning-based evaluation for lane departure warning system considering driving characteristics

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART D-JOURNAL OF AUTOMOBILE ENGINEERING 2024年第5期238卷 1201-1218页

作者： Jin, Xianjian Wang, Qikang Yan, Zeyuan Yang, Hang Wang, Jinxiang Yin, Guodong Shanghai Univ Sch Mechatron Engn & Automation Shanghai Key Lab Intelligent Mfg & Robot Shanghai Peoples R China Jilin Univ State Key Lab Automot Simulat & Control Changchun Peoples R China Southeast Univ Sch Mech Engn Nanjing Peoples R China Shanghai Univ Sch Mechatron Engn & Automation Shanghai Key Lab Intelligent Mfg & Robot 99 Shanghai Univ Rd Shanghai 200072 Peoples R China

Misunderstanding the driver behavior in the next short time is the primary reason of the false warning for the lane departure warning system. This paper proposes a learning-based evaluation to predict whether the driver notices the deviation of the vehicle and takes corrective actions. First, statistical Gaussian model and K-means clustering method are utilized to classify driving style of drivers and determine warning areas based on key driving parameters extracted in driving scenarios. Then, according to the vehicle trajectory in the warning area and the time of lane crossing (TLC) value of the two warning area boundaries, an advanced horizontal dual-area warning (HDAW) model that is trained by bi-direction long short-term memory (BiLSTM) originated from recurrent neural network (RNN) is applied to predict the lane departure and corrective behavior of driver. The personalized warning strategy is finally developed by considering driver characteristics, which allows the warning system to adapt to different driving styles of drivers. Natural driving data from 57 drivers in the experimental driving simulator are collected to train personalized prediction and verify proposed evaluation method. The recent directional sequence of piecewise lateral slopes (DSPLS) and traditional TLC are also researched and compared. Experimental results show that the proposed approach has as low as false alarm rate of 3.97% and can improve prediction accuracy approximately 41.39% over DSPLS method.

关键词： Lane departure warning system driver behavior driver adaptation learning approach

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Quasi-Synchronization of Fractional Multiweighted Coupled Neural Networks via Aperiodic Intermittent control

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IEEE TRANSACTIONS ON CYBERNETICS 2024年第3期54卷 1671-1684页

作者： Wei, Chen Wang, Xiaoping Hui, Meng Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan Peoples R China Changan Univ Sch Elect & Control Xian 710064 Peoples R China

This article investigates the quasi-synchronization for fractional multiweighted coupled neural networks (FMCNNs) with discontinuous activation functions and mismatched parameters. First, under the generalized Caputo fractional-order derivative operator, a novel piecewise fractional differential inequality is established to study the convergence of fractional systems, which significantly extends some related published results. Subsequently, by exploiting the new inequality and Lyapunov stability theory, some sufficient quasi-synchronization conditions of FMCNNs are presented by aperiodic intermittent control. Meanwhile, the exponential convergence rate and synchronization error's bound are given explicitly. Finally, the validity of theoretical analysis is confirmed by numerical examples and simulations.

关键词： Synchronization Biological neural networks Behavioral sciences Fractional calculus Convergence Standards Power system stability Aperiodic intermittent control discontinuous activation functions fractional multiweighted neural networks mismatched parameters quasi-synchronization

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Consensus of discrete-time heterogeneous multi-agent systems in noisy environments without velocity transmission

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ASIAN JOURNAL OF control 2025年第0期

作者： Chen, Jiali Zong, Xiaofeng Hou, Xuping Wang, Zi-Xuan China Univ Geosci Sch Automat Wuhan Peoples R China Hubei Key Lab Adv Control & Intelligent Automation Wuhan Peoples R China Minist Educ Engn Res Ctr Intelligent Technol GeoExplorat Wuhan Peoples R China

This paper investigates consensus control of discrete-time heterogeneous multi-agent systems with multiplicative noise. As the frequent absence of velocity sensors in real industrial environments, a control protocol is developed using absolute velocity and relative position measurement information. Then, the consensus control issue is reformulated as the stability issue of stochastic difference equations. By choosing an appropriate Lyapunov function, the above stability issue is studied, and the sufficient conditions for leader-free and leader-following discrete-time heterogeneous multi-agent systems to achieve both mean-square and almost-sure consensus are derived, respectively. Finally, numerical simulations are provided to validate the effectiveness of the main results.

关键词： consensus discrete-time heterogeneous multi-agent systems leader-following leader-free multiplicative noise

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Optimal Output Synchronization of Euler-Lagrange Systems With Uncertain Time-Varying Quadratic Cost Functions

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IEEE TRANSACTIONS ON CYBERNETICS 2025年第4期55卷 1648-1658页

作者： Jiang, Liangze Wu, Zheng-Guang Wang, Lei Xu, Yong Che, Wei-Wei Zhejiang Univ Coll Control Sci & Engn Hangzhou 310027 Peoples R China Beijing Inst Technol Sch Automation Beijing 100081 Peoples R China Northeastern Univ State Key Lab Synthet Automation Proc Ind Shenyang 110819 Peoples R China Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China

In this article, we study the optimal output synchronization problem (OOSP) for uncertain networked Euler-Lagrange (EL) systems. Specifically, the system outputs are expected to be synchronized at the solution of an uncertain distributed time-varying quadratic optimization problem, where each local time-varying cost function includes uncertain parameters. From a centralized perspective, we first develop a controller with adaptive control gains to guide the output of a double-integrator system toward the time-varying optimal solution. By employing the modified average estimators, we extend the centralized design to a distributed implementation to address the OOSP for uncertain EL systems. Using matrix trace properties and composite Lyapunov analysis, we prove that the system outputs can asymptotically converge to the desired time-varying optimal solution. Two examples are used to verify the proposed designs.

关键词： Cost function Time-varying systems Uncertainty Synchronization Vectors Multi-agent systems Electronic mail Location awareness Laplace equations Costs Distributed optimization Euler-Lagrange (EL) system optimal output synchronization time-varying cost function uncertainties

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Grid-connection damping strategy for grid-forming VSG based on angular frequency lead-lag feedforward compensation

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2025年 167卷

作者： Shi, Rongliang Liang, Chuanfeng Li, Junhui Zhong, Zhixian Bai, Xinyuan Guilin Univ Technol Educ Dept Guangxi Zhuang Autonomous Reg Key Lab Adv Mfg & Automation Technol Guilin 541006 Peoples R China Northeast Elect Power Univ Key Lab Modern Power Syst Simulat & Control & Rene Minist Educ Jilin 132011 Peoples R China

The primary frequency modulation coefficient of the grid-forming virtual synchronous generator (GFVSG) is coupled with the virtual damping coefficient, which leads to the problem that it is difficult to take into account both the dynamic oscillation and the steady-state deviation of the grid-connected active power (GCAP). To address this issue, an improved GFVSG grid-connected damping strategy based on angular frequency lead-lag feedforward compensation is proposed in this paper. This strategy introduces the angular frequency lead-lag feedforward compensation link into the GCAP closed-loop control loop of GFVSG, and improves both the GCAP dynamic and steady state response performances of GFVSG through reasonable adjustment of the lead-lag compensation parameters. Finally, according to the comparison results of simulation and experimental tests, it can be seen that the proposed grid-connected damping strategy can effectively solve the GCAP dynamic oscillation and steady-state deviation problems existing in GFVSG under the step disturbances of active power command and grid frequency.

关键词： Grid-forming Virtual Synchronous Generator (GFVSG) Dynamic oscillation Steady-state deviation Grid-connected active power (GCAP) Lead-lag feedforward compensation

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Graph Relational Reinforcement Learning for Mobile Robot Navigation in Large-Scale Crowded Environments

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2023年第8期24卷 8776-8787页

作者： Liu, Zhe Zhai, Yu Li, Jiaming Wang, Guangming Miao, Yanzi Wang, Hesheng Shanghai Jiao Tong Univ AI Inst MoE Key Lab Artificial Intelligence Shanghai 200240 Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221116 Peoples R China Shanghai Jiao Tong Univ Dept Automation Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Minist Educ Dept AutomationKey Lab Syst Control & Informat Pr Shanghai Engn Res Ctr Intelligent Control & Manage Shanghai 200240 Peoples R China

Mobile robot autonomous navigation in large-scale environments with crowded dynamic objects and static obstacles is still an essential yet challenging task. Recent works have demonstrated the potential of using deep reinforcement learning to enable autonomous navigation in crowds. However, only considering the human-robot interactions results in short-sighted and unsafe behaviors, and they typically use hand-crafted features and assume the global observation range, leading to large performance declines in large-scale crowded environments. Recent advances have shown the power of graph neural networks to learn local interactions among surrounding objects. In this paper, we consider autonomous navigation task in large-scale environments with crowded static and dynamic objects (such as humans). Particularly, local interactions among dynamic objects are learned for better-understanding their moving tendency and relational graph learning is introduced for aggregating both the object-object interactions and object-robot interactions. In addition, local observations are transformed into graphical inputs to achieve the scalability to various number of surrounding dynamic objects and various static obstacle patterns, and the globally guided reinforcement learning strategy is introduced to achieve the fixed-sized learning model even in large-scale complex environments. Simulation results validate our generalizability to various environments and advanced performance compared with existing works in large-scale crowded environments. In particular, our method with only local observations performs better than the benchmarks with global complete observability. Finally, physical robotic experiments demonstrate our effectiveness and practical applicability in real scenarios.

关键词： Navigation Task analysis Mobile robots Autonomous robots Reinforcement learning Scalability Training Crowded environment reinforcement learning relational graph learning robot navigation

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Robust Adaptive Event-Triggered Fault-Tolerant Consensus control of Multiagent Systems With a Positive Minimum Interevent Time

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2023年第7期53卷 4003-4014页

作者： Hou, Qinghua Dong, Jiuxiang Northeastern Univ Coll Informat Sci & Engn State Key Lab Synthet Automation Proc Ind Shenyang Peoples R China Northeastern Univ Key Lab Vibrat & Control Aeroprop Syst Minist Educ Shenyang Peoples R China

The distributed fault-tolerant (FT) consensus control problem of linear multiagents with disturbances is considered in this article. For undirected graphs, first, by introducing adaptive control coefficients, multiagent reliable control can be carried out fully distributed, removing the assumption that global information should be known prior. Furthermore, different from existing consensus FT studies, the limitation of continuous communication among agents is removed by developing an open-loop estimation and event-triggering mechanism (ETM). Particularly, distinct from some dwell-time methods that enforce an interevent time greater than zero at the expense of asymptotic stability, by introducing timer variables, positive interevent time and asymptotic stability can be guaranteed simultaneously by the proposed ETM in the absence of disturbances. Furthermore, a minimum positive trigger interval can be maintained for each agent even in the presence of disturbances, indicating the robustness of the event-triggered strategy. It is demonstrated that the suggested event-triggered control method performs reliable disturbance suppression for all agents in a completely distributed way with intermittent communication while excluding the Zeno behavior. Moreover, we try to generalize our results to directed strong connectivity. Finally, simulation examples are carried out to illustrate the efficacy of the suggested scheme.

关键词： Actuators Behavioral sciences Asymptotic stability Eigenvalues and eigenfunctions Symmetric matrices Consensus control Computational modeling Event-triggered control fault-tolerant control (FTC) multiagent systems (MASs)

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Effect of contact surface roughness on friction self-excited vibration of the propulsion shaft-bearing system

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JOURNAL OF VIBRATION AND control 2025年

作者： Xie, Zhihao Huang, Qianwen Zhao, Zeyu Gao, Kaiyan Wuhan Univ Sci & Technol Sch Machinery & Automation Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan Peoples R China Wuhan Univ Sci & Technol Sch Machinery & Automat Key Lab Met Equipment & Control Technol Minist Educ 947 Heping Rd Wuhan 430081 Peoples R China

An appropriate assessment of the self-excited vibration of the shaft-bearing system is crucial for effectively enhancing the reliability of ships during operation. The characteristics of self-excited vibration are not only influenced by inadequate lubrication, but also by the roughness of the contact surface between the bearing and shaft. Therefore, a lubrication model that takes into account surface roughness, velocity-dependent friction model derived from experimental data, and a dynamic model for the shaft-bearing system is established. This paper discusses the effects of rotational speed and pressure on self-excited vibration by combining transient amplitude, harmonic frequency, and phase diagrams, and conducts experimental validation. It analyzes the relationship between surface roughness and the lubrication characteristics of the bearing. The dynamic equations of the shaft-bearing are combined to discuss the influence of surface roughness on self-excited vibration. This research indicates that changes in rotational speed and positive pressure can lead to frictional instability, resulting in self-excited vibration and "stick-slip" in the shaft-bearing system. Furthermore, the roughness of the contact area significantly influences system vibration, resulting in a decrease in the vibration amplitude of both the shaft and bearing. Notably, while the reduction in vibration amplitude for the shaft is subtle, that of the bearing exhibits a more pronounced decrease of approximately 40%. A smaller vibration amplitude for the bearing is observed as its roughness falls within the range of Ra2.4 to Ra3.2.

关键词： Friction self-excited vibration contact surface roughness shaft-bearing system experimental verification vibration characteristics

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