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Distributed Leaderless Optimal Output Consensus of Heterogeneous Multi-Agent Systems

Journal of Systems science & Complexity 2025年第2期38卷 671-690页

作者： ZHANG Liping ZHANG Huanshui XIE Lihua College of Electrical Engineering and Automation Shandong University of Science and Technology School of Control Science and Engineering Shandong University School of Electrical and Electronic Engineering Nanyang Technological University

The distributed optimal output synchronization problem for the leaderless heterogeneous multi-agent system with a general global cost function is investigated for the first time by linear quadratic(LQ) optimal control theory. Conventional algorithms for heterogeneous systems are quite complex, requiring the design of a virtual reference generator and the solving of regulation *** paper presents a novel distributed asymptotically optimal controller by incorporating the design of distributed observer and feedforward controller. A general form of the distributed controller is obtained by solving an augmented algebraic Riccati equation, which is parallel to classical optimal control theory. The optimal topology is an arbitrary directed graph containing only a spanning tree. It is shown that the proposed algorithms outperform the traditional consensus methods in the convergence speed by selecting proper observer gain matrices, and eliminate the reliance on the nonzero eigenvalues of Laplacian matrix. Simulation example further demonstrates the effectiveness of the proposed scheme and a faster superlinear convergence speed than the existing algorithm.

关键词： Distributed feedforward control heterogeneous systems leaderless output consensus optimal control

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Distributed Cooperative control for Human-Unmanned Aerial Vehicle Swarm Teaming in Target Tracking∗

Distributed Cooperative Control for Human-Unmanned Aerial Ve...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： He, Hangxuan Huo, Mengzhen Duan, Haibin School of Automation Science and Electrical Engineering Beihang University Beijing100083 China School of Automation Science and Electrical Engineering Beihang University Science and Technology on Aircraft Control Laboratory Beijing100083 China

ISBN: (纸本)9781665481090

Over the last decade, the relationship between humans and cyber-physical systems has grown closer, particularly in fields such as manufacturing and transportation. This paper presents a control framework within the engineering domain, wherein a human operator collaborates with a swarm of unmanned aerial vehicles (UAVs) to achieve a shared goal. First, we construct a human-swarm mutual trust model that empowers both parties with a degree of autonomy. Second, we adopt a distributed optimization algorithm integrated with control barrier functions to manage the swarm's motion. The cooperative control framework is demonstrated in a 3D scenario, and simulation results verify the feasibility of the proposed method. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Memristive Spiking Neural Network Circuit for Bio-inspired Navigation Based on Spatial Cognitive Mechanisms

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IEEE Transactions on Biomedical Circuits and Systems 2024年第3期19卷 686-698页

作者： Chen, Zhanfei Wang, Xiaoping Wang, Zilu Yang, Chao Huang, Tingwen Lai, Jingang Zeng, Zhigang School of Mechanical Engineering and Automation Shenzhen518055 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation China Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan430074 China Guangxi University of Science and Technology School of Computer Science and Technology Liuzhou545006 China Shenzhen University of Advanced Technology School of Computer Science and Control Engineering Shenzhen518055 China

Cognitive navigation,a high-level and crucial function for organisms' survival in nature,enables autonomous exploration and navigation within the environment. However,most existing works for bio-inspired navigation are implemented with non-neuromorphic computing. This work proposes a bio-inspired memristive spiking neural network (SNN) circuit for goal-oriented navigation,capable of online decision-making through reward-based learning. The circuit comprises three primary modules. The place cell module encodes the agent's spatial position in real-time through Poisson spiking;the action cell module determines the direction of subsequent movement;and the reward-based learning module provides a bio-inspired learning method adaptive to delayed and sparse rewards. To facilitate practical application,the entire SNN is quantized and deployed on a real memristive hardware platform,achieving about a 21× reduction in energy consumption compared to a typical digital acceleration system in the forward computing phase. This work offers an implementation idea of neuromorphic solution for robotic navigation application in low-power scenarios. © 2007-2012 IEEE.

关键词： Intelligent robots

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Dynamic learning from neural PID output-feedback control for a lower limb exoskeleton rehabilitation robot

Dynamic learning from neural PID output-feedback control for...

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2024 China automation Congress, CAC 2024

作者： Li, Wen Zhang, Xinhao He, Weitian Zou, Chaobin Yang, Qinchen Zhang, Fukai Cheng, Hong Wang, Cong School of Control Science and Engineering Shandong University Jinan China School of Automation Engineering University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9798350368604

With the intensification of population aging and the increasing number of patients with lower limb dysfunction, the research and precise control of lower limb rehabilitation robots have become increasingly important. In this study, a sitting and lying lower limb exoskeleton robot model is developed based on the CoppeliaSim platform. For the nonlinear system of a two-degree-of-freedom single-leg robot with uncertainty, an improved PID control method based on deterministic learning is proposed. Under the condition of persistent excitation, this control method accurately identifies the unknown dynamic characteristics of the system by introducing a neural network, ensuring precise control of lower limb movements. Learning-based PID controllers are constructed using the gained knowledge to achieve fast, smooth tracking and greatly improve the safety of rehabilitation control. The results of simulation experiments show that the proposed control strategy in this paper is effective. © 2024 IEEE.

关键词： Exoskeleton (Robotics)

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Robust control for Interval Type-2 T-S Fuzzy Discrete Systems with Input Delays and Cyber Attacks

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Journal of Systems science & Complexity 2023年第4期36卷 1443-1462页

作者： LIU Chuang WU Jinxia YANG Weidong School of Automation University of Science and Technology BeijingBeijing 100083China College of Control Science and Engineering BoHai UniversityJinzhou 121001China College of Science Liaoning University of TechnologyJinzhou 121001China

This paper focuses on the robust control issue for interval type-2 Takagi-Sugeno(IT2 T-S)fuzzy discrete systems with input delays and cyber *** lower and upper membership functions are first utilized to IT2 fuzzy discrete systems to capture parameter *** considering the influences of input delays and stochastic cyber attacks,a newly fuzzy robust controller is ***,the asymptotic stability sufficient conditions in form of LMIs for the IT2 closed-loop systems are given via establishing a Lyapunov-Krasovskii ***,a solving algorithm for obtaining the controller gains is ***,the effectiveness of the developed IT2 fuzzy method is verified by a numerical example.

关键词： Asymptotic stability fuzzy robust control input delays IT2 T-S fuzzy discrete systems stochastic cyber attacks

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Obstacle-circumventing adaptive control of a four-wheeled mobile robot subjected to motion uncertainties

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Frontiers of Mechanical engineering 2023年第3期18卷 123-143页

作者： Yiming YAN Shuting WANG Yuanlong XIE Hao WU Shiqi ZHENG Hu LI School of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China

To achieve the collision-free trajectory tracking of the four-wheeled mobile robot(FMR),existing methods resolve the tracking control and obstacle avoidance *** the synergistic robustness and smooth navigation of mobile robots subjected to motion uncertainties in a dynamic environment using this non-cooperative processing method is *** address this challenge,this paper proposes an obstacle-circumventing adaptive control(OCAC)***,a novel anti-disturbance terminal slide mode control with adaptive gains is formulated,incorporating specified control laws for different *** formulation guarantees rapid convergence and simultaneous chattering *** introducing sub-target points,a new sub-target dynamic tracking regression obstacle avoidance strategy is presented to transfer the obstacle avoidance problem into a dynamic tracking one,thereby reducing the burden of local path searching while ensuring system stability during obstacle *** experiments demonstrate that the proposed OCAC method can strengthen the convergence and obstacle avoidance efficiency of the concerned FMR system.

关键词： four-wheeled mobile robot obstacle-circumventing adaptive control adaptive anti-disturbance terminal sliding mode control sub-target dynamic tracking regression obstacle avoidance

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Strong Structural controllability Based on Leader-Follower Framework

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Journal of Systems science & Complexity 2023年第4期36卷 1498-1518页

作者： QI Wei JI Zhijian LIU Yungang LIN Chong Insitute of Complexity Science College of AutomationQingdao UniversityQingdao 266071China Shandong Key Laboratory of Industrial Control Technology Qingdao UniversityQingdao 266071China School of Control Science and Engineering Shandong UniversityJinan 250061China

In this paper,the strong structural controllability of the leader-follower framework is ***,the authors analyze different edge augmentation methods to preserve the strong structural controllability of the path-bud *** following four cases are considered:Adding edges from the path to the bud;adding edges from the bud to the path;adding the reverse or forward edges to the path or bud;and adding both the reverse and forward edges to the path or *** sufficient conditions are derived for the strong structural controllability of the new topologies which are generated by adding different *** addition,it is proved that rank[A B]=n is a necessary condition for the strong structural ***,three examples are given to verify the effectiveness of the main results.

关键词： Edge augmentation leader-follower framework path-bud topology strong structural controllability

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Dynamic Event-Triggered Consensus control for Input Constrained Multi-Agent Systems With a Designable Minimum Inter-Event Time

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 649-660页

作者： Meilin Li Yue Long Tieshan Li Hongjing Liang C.L.Philip Chen the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China IEEE the Yangtze Delta Region Institute University of Electronic Science and Technology of ChinaHuzhou 313000 the Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing 100089China the School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006

This paper investigates the consensus control of multi-agent systems(MASs) with constrained input using the dynamic event-triggered mechanism(ETM).Consider the MASs with small-scale networks where a centralized dynamic ETM with global information of the MASs is first ***,a distributed dynamic ETM which only uses local information is developed for the MASs with large-scale *** is shown that the semi-global consensus of the MASs can be achieved by the designed bounded control protocol where the Zeno phenomenon is eliminated by a designable minimum inter-event *** addition,it is easier to find a trade-off between the convergence rate and the minimum inter-event time by an adjustable ***,the results are extended to regional consensus of the MASs with the bounded control *** simulations show the effectiveness of the proposed approach.

关键词： Constrained input designable minimum inter-event time directed communication topology dynamic event-triggered mechanism MASs consensus control

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EFFECT OF CENTER-OFFSET ARC POLE SHOE SHAPES ON TORQUE RIPPLE AND EDDY-CURRENT LOSS OF CONSEQUENT POLE ROTOR

EFFECT OF CENTER-OFFSET ARC POLE SHOE SHAPES ON TORQUE RIPPL...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Li, Haien Yan, Liang Liu, Xiaoshuai Xiang, Pengjie He, Xinghua Du, Nannan Xuxu, Yang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing China

Traditional consequent pole motor has the advantages of less magnetic costs, small magnetic resistance and strong inductance. It is widely studied in the design of the electrical propulsion system. However, it has the problem of uneven distribution of air gap magnetic flux density. It is locally distributed by square waves, causing the high -level harmonic problem, increasing the torque pulse and vortex loss of the motor. This paper show the design principles of the center-offset arc pole. And the limited element simulation of the motor of different eccentric spacing. The results show that compared with the consequent pole, increasing the center-offset distance can reduce the torque ripple and vortex loss. © The Institution of engineering & Technology 2024.

关键词： Magnetic flux

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Enhancing Unmanned Ground Vehicle Evasion Through Generative Adversarial Imitation Learning in UAV Pursuit Scenarios

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Guidance,Navigation and control 2025年第1期05卷 149-154页

作者： Shuai Hao Zhaoyu Zhang Mengzhen Huo Chen Wei School of Automation Science and Electrical Engineering Beihang University National Key Laboratory of Aircraft Integrated Flight Control Beihang University

This study focuses on enhancing the evasion capabilities of unmanned ground vehicles(UGVs) using Generative Adversarial Imitation Learning(GAIL). The UGVs are trained to evade unmanned aerial vehicles(UAVs). A decision-making neural network has been trained via GAIL to refine evasion strategies with expert demonstrations. The simulation environment was developed with OpenAI Gym and calibrated with real-world data for the improvement of accuracy. The integrated platform including the proposed algorithm was tested in flight experiments. Results showed that the UGVs could effectively evade UAVs in the complex and dynamic environment.

关键词： Unmanned ground vehicles unmanned aerial vehicles imitation learning flight experiment

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