Article
Engineering, Multidisciplinary
Guanglei Zhao, Changchun Hua, Shuang Liu
Summary: This paper investigates the consensus problem in multi-agent systems using sampled-data dynamic output feedback control. A distributed control law is designed based on sampled relative output information between neighboring agents. A closed-loop system model with hybrid dynamics is constructed for consensus analysis and choice of sampling period. Lyapunov-based analysis is presented to develop stability conditions. Compared to existing works, observer design is not required, and only sampled relative output information is used, with the ability to explicitly compute the maximum allowable sampling period.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Fenglan Sun, Chuan Lu, Wei Zhu, Juergen Kurths
Summary: This paper addresses the issue of dynamic mean-square consensus for second-order hybrid multi-agent systems with time-varying delays and multiplicative noises. New distributed control protocols are designed based on data-sampled information of neighbor agents. The proposed method achieves dynamic consensus under both fixed and switching topologies by using the error system based on Laplacian matrix. Several sufficient conditions for the dynamic mean-square consensus are obtained using stochastic system theory, Lyapunov stability method, and linear matrix inequality theory. Simulations are conducted to demonstrate the effectiveness of the proposed methods.
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Kecai Cao, Chunjiang Qian, Juping Gu, Liang Hua
Summary: The sampled-data output consensus problem was addressed within a co-design framework, incorporating control gains and sampling periods. By introducing a scaled coordinate transformation and directly designing sampled-data controllers in discrete-time domain, the method allows for greater flexibility in digital implementation compared to previous work. Simulation studies demonstrate the effectiveness of the co-designed sampled-data output controllers with various sampling periods.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Suoxia Miao
Summary: This paper investigates the consensus issue for multi-agent systems on matrix-weighted directed fixed and undirected switching network topologies using a sampled data control method. The distributed control laws are designed for each topology. Consensus conditions based on the sampling period and Laplacian matrix eigenvalues are derived for the directed fixed network topology, while consensus conditions based on the sampling period and switched network topologies are established for the undirected switching network topology. Two simulation examples are provided to validate the results.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Mathematics, Applied
Can Zhao, Xinzhi Liu, Shouming Zhong, Kaibo Shi, Daixi Liao, Qishui Zhong
Summary: A novel sampled-data event-triggered control method for multi-agent systems is proposed, which eliminates Zeno behavior and integrates node-based and non-node-based triggering time instants. The method considers cyber attacks and achieves leader-following consensus. Numerical examples validate the effectiveness of the proposed approach.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Engineering, Mechanical
Zhiyu Duan, Airong Wei, Xianfu Zhang, Rui Mu
Summary: This paper investigates the consensus problem in nonlinear multi-agent systems with output delay and false data injection attacks using sampled-data output feedback control, where only the delayed sampling outputs are available. Firstly, an improved compensator is constructed to provide control signals using the available information without continuous communication with neighbors. Secondly, compensator-based sampled-data control protocols with different time-varying gains are proposed for both absence and presence of false data injection attacks. The proposed protocols, in combination with the Lyapunov-Krasovskii functional approach, achieve consensus and compensate for the effect of output delay and attack signals. The results are further extended to multi-agent systems with more general nonlinearities, with arbitrary positive constants as the sampling period and output delay.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Chen Gao, Zidong Wang, Xiao He, Dong Yue
Summary: This paper addresses the fault-tolerant consensus control problem for linear continuous-time multi-agent systems with data privacy preserving constraints and develops a novel dynamic quantization-based DPP scheme from a control-theoretic perspective. A fault-tolerant controller is designed using the sampled, quantized, released, received and recovered data under the developed DPP scheme, ensuring consensus of MASs with limited data transmission. Numerical examples and comparative analysis demonstrate the effectiveness of the developed consensus control scheme.
Article
Engineering, Electrical & Electronic
Yao Zou, Zongyu Zuo, Kewei Xia, Michael V. V. Basin
Summary: This article studies the interval consensus of multi-agent systems using sampled data. Two sampled-data distributed control protocols are proposed to achieve consensus inside a given interval, considering generic saturations with heterogeneity and asymmetry. These protocols allow asynchronous sampling without requiring global clock synchronization and have been validated through simulation examples.
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS
(2022)
Article
Automation & Control Systems
Yanyan Ye, Siqin Liao, Yuanqing Wu, Mali Xing
Summary: This paper investigates the consensus problem of fractional-order multi-agent systems with the order alpha satisfying alpha is an element of (0, 1]. A novel distributed control protocol is constructed, which utilizes only past sampled position data of neighbors. Based on Laplace transform, Mittag-Leffler function, and matrix theory, necessary and sufficient criteria for consensus are established, depending on the order, coupling gains, sampling period, and communication topology. The intervals of coupling gains and sampling period for achieving consensus are presented. Numerical simulations validate the theoretical results.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Computer Science, Interdisciplinary Applications
S. Lavanya, S. Nagarani
Summary: This paper investigates the leader-following consensus of multi-agent systems, considering the sampling effects of the agents' actuators. It uses sampled-data control and time-dependent Lyapunov-Krasovskii functionals for consensus analysis, establishing less conservative consensus conditions through linear matrix inequalities. By constructing a looped Lyapunov Krasovskii functional and designing suitable controllers, closed-loop dynamics for consensus analysis are achieved effectively.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Automation & Control Systems
Xiao-Jie Peng, Yong He
Summary: This paper investigates the aperiodic sampled-data consensus control problems for nonlinear homogeneous and heterogeneous multi-agent systems (MASs). The consensus conditions for homogeneous MASs are derived using a two-sided-looped functional, considering the intervals between delta(t) and delta(tk) as well as delta(t) and delta(tk+1). Two aperiodic sampled-data controllers are designed, and upper bound estimates for the maximum allowable sampling interval are provided. For heterogeneous MASs, a bounded consensus tracking criterion is derived based on the improved looped functional method. Corresponding heterogeneous sampled-data controllers are designed for each follower to ensure exponential convergence of the consensus tracking error to a bounded ellipsoid region. Three illustrative examples are presented to demonstrate the efficiency and superiority of the proposed results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Menghao Qu, Qiangde Wang, Chunling Wei
Summary: This paper investigates the sampled-data-based event-triggered consensus problem of second-order multi-agent systems (MASs) with sampled position data using impulsive control. Two types of sampled-data-based event-triggered impulsive control protocols are proposed, which utilize only sampled position data. A novel transmission scheme is designed to ensure the existence of maximum length triggering intervals, regulated by parameters in the triggering function. The designed impulsive control scheme achieves consensus of second-order MASs with lower transmission and control updating frequency compared to the periodic impulsive control scheme. Sufficient conditions on communication topology, triggering interval length, and control gains are derived for achieving sampled-data-based event-triggered consensus.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Information Systems
Chuanjian Li, Xiaofeng Zong
Summary: This paper focuses on the group consensus of multi-agent systems (MASs) consisting of two groups in additive noise environments. A control protocol is proposed based on the state information corrupted by additive noises. Sufficient and necessary conditions are obtained for pure group consensus and hybrid group consensus. The study reveals that the influence between the two groups should be attenuated for achieving group consensus.
SCIENCE CHINA-INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Kewei Zhang, Yuanyuan Zhang, Renfu Li, Guanrong Chen
Summary: This paper studies the sampled-data-based consensus control problem of multi-agent systems (MASs) with multiplicative noise and time-delays, developing a discretization-reconnection method and establishing sufficient conditions for mean-square and almost sure consensus, and verifying the theoretical results through numerical simulations.
INFORMATION SCIENCES
(2022)
Article
Automation & Control Systems
Huanyu Zhao, Lei Wang, Hongbiao Zhou, Dongsheng Du
Summary: This paper investigates consensus in a sampled-data heterogeneous multi-agent system. By discretizing the continuous-time networked system and transforming the multi-agent system into a reduced-order error system, sufficient conditions for consensus are obtained for networked systems with and without velocity measurement. Simulations confirm the effectiveness of the results.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Qing Wang, Xiwang Dong, Jinhu Lu, Zhang Ren
Summary: This paper studies the problem of time-varying output formation tracking for directed multi-agent systems, where the leader has unknown input and each follower has nonidentical dynamics. The main objective of this paper is to construct a fully distributed controller that enables the followers to track the leader's output and realize the expected formation simultaneously. Two adaptive observers are constructed to estimate the states of the leader and followers, respectively, by exploiting neighboring information and local estimation. A fully distributed TVOFT control protocol is developed using the distributed observers and the expected time-varying formation vector, and the parameters of the controller are designed through a three-step algorithm. The TVOFT criteria for the considered closed-loop multi-agent systems are obtained based on the Lyapunov stability theory and output regulation method.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Guoliang Zhu, Kexin Liu, Haibo Gu, Lei Chen, Jinhu Lu
Summary: This article investigates the consensus-based formation control problem in multi-agent systems with unknown disturbances. The proposed node-based adaptive controllers eliminate the effect of disturbances and avoid continuous communications. It is shown that the formation errors tend to zero when the derivatives of disturbances belong to Script capital L2 $$ {\mathcal{L}}_2 $$ space or are bounded by a small threshold. Zeno behaviors and global information are excluded. Numerical simulations validate the effectiveness of the proposed approaches.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Yingqing Pei, Ye Tao, Haibo Gu, Jinhu Lu
Summary: This paper proposes three distributed algorithms under three quantization cases to seek Nash equilibrium in aggregative games with quantization constraints based on doubly stochastic communication topology networks. It is proven that the actions of players will eventually converge to Nash equilibrium under the conditions of vanishing step size and strong monotonicity, and the convergence rates of the three quantization cases are analyzed. Numerical experiments on PHEVs are conducted to validate the effectiveness of the proposed algorithms, and it is found that the convergence effect of adaptive quantization is better than the other two quantization cases.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Engineering, Electrical & Electronic
Deyuan Liu, Hao Liu, Jinhu Lu, Frank L. Lewis
Summary: This paper investigates the optimal formation control of a heterogeneous multiagent system consisting of multiple quadrotors and ground vehicles via reinforcement learning to achieve the time-varying formation under switching topologies. A distributed observer is constructed to generate references for each vehicle to form time-varying formation using local information, and the convergence of the observer under switching topologies is proven. Reinforcement learning methods are provided for the heterogeneous vehicle group to realize optimal tracking control without knowledge of the vehicle dynamics model. Simulation tests confirm the effectiveness of the proposed method.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Computer Science, Artificial Intelligence
Zhihong Fang, Shaolin Tan, Yaonan Wang, Jinhu Lu
Summary: In this paper, a neural network based learning method is proposed for link prediction using 1-hop neighborhood information. The method extracts the 1-hop neighborhood of a target link as the enclosing subgraph, encodes the subgraph into different topological features, and trains a fully connected neural network for link prediction. Experimental results show that the proposed method outperforms heuristic-based methods and achieves similar performance to state-of-the-art learning-based methods. Additionally, the features can be concatenated with attribute vectors to greatly improve link prediction performance in attributed graphs.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Review
Engineering, Multidisciplinary
JianYuan Wang, KeXin Liu, YuCheng Zhang, Biao Leng, JinHu Lu
Summary: The rapid development of deep learning has greatly facilitated production and life, but the reliance on massive labels for training models hinders further progress. Few-shot learning, which can achieve high-performance models with limited samples, offers a solution for scenarios lacking data. This paper provides an overview of recent few-shot learning algorithms and proposes a taxonomy. The paper discusses the significance of few-shot learning, categorizes methods based on different implementation strategies, explores their applications in computer vision, human-machine language interaction, and robot actions, and analyzes existing approaches based on evaluation results on miniImageNet.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Automation & Control Systems
Bing Mao, Xiaoqun Wu, Jinhu Lu, Guanrong Chen
Summary: This article investigates the uniformly predefined-time bounded consensus of leader-following multiagent systems with unknown system nonlinearity and external disturbance. Distributed adaptive fuzzy control is used to analyze and design the system, achieving global consensus within a predefined time.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Jialing Zhou, Yuezu Lv, Guanghui Wen, Jinhu Lu, Dezhi Zheng
Summary: This article investigates the distributed Nash equilibrium seeking problem in multicoalition games, considering the agreement demand within coalitions. The proposed algorithm achieves linear convergence and unifies networked games among individual players and distributed optimization in a consistent-constrained multicoalition game framework.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Ming Cheng, Hao Liu, Qing Gao, Jinhu Lu, Xiaohua Xia
Summary: This article proposes an optimal controller for a team of underactuated quadrotors with multiple active leaders in containment control tasks. The quadrotor dynamics are underactuated, nonlinear, uncertain, and subject to external disturbances. The proposed controller consists of a position control law to guarantee the achievement of position containment and an attitude control law to regulate the rotational motion, which are learned via off-policy reinforcement learning using historical data from quadrotor trajectories. The closed-loop system stability can be guaranteed by theoretical analysis. Simulation results of cooperative transportation missions with multiple active leaders demonstrate the effectiveness of the proposed controller.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Qing Wang, Yongzhao Hua, Xiwang Dong, Peixuan Shu, Jinhu Lu, Zhang Ren
Summary: This article investigates the finite-time output time-varying formation tracking problem for heterogeneous nonlinear multiagent systems. A finite-time observer is constructed to estimate the leader's state and compensate for unknown input. Based on the developed observers and adaptive output regulation method, a novel finite-time distributed output tracking controller is proposed. The results show that the expected finite-time output formation tracking can be achieved within a finite time for the considered heterogeneous nonlinear multiagent systems.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Kunrui Ze, Wei Wang, Kexin Liu, Jinhu Lu
Summary: This article presents a novel method for optimization-based obstacle avoidance and distributed regular polygon time-varying formation control for multiple unmanned aerial vehicle systems (UAVs) in clutter environment. The method involves a leader-following structure with a directed communication graph, real-time trajectory planning for the leader UAV, and an optimization-based safe trajectory and formation size online planning algorithm. The method also includes distributed smooth adaptive filters to estimate the safe trajectory and formation size, as well as a geometric tracking controller for each UAV. Experimental results demonstrate the effectiveness of the proposed method.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Zhi Feng, Guoqiang Hu, Xiwang Dong, Jinhu Lu
Summary: This article addresses finite-time connectivity-preserving rendezvous problems of networked uncertain Euler-Lagrange systems, where two types of time-varying leaders are investigated, and only a subset of followers can have access to the leader's trajectory. The distributed estimation and control architecture is then established to solve this problem with an emphasis on the settling-time estimation.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Zhi Feng, Guoqiang Hu, Xiwang Dong, Jinhu Lu
Summary: This article presents the design of adaptively distributed Nash Equilibrium (NE) seeking algorithms for heterogeneous general linear multi-agent systems in noncooperative games. The algorithms adjust the edges of the graph to deal with nonidentical dynamics and seeking NE. Global asymptotic convergence is achieved through leveraging monotone and matrix properties.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Juyi Li, Xiaoqun Wu, Su Zhong, Ruguo Fan, Jie Hu, Jinhu Lu
Summary: This paper introduces the use of hypergraphs and game theory to study the investment environment. The results obtained from empirical analysis provide meaningful insights for corporate decision-making and government regulation.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Dandan Wang, Jialing Zhou, Guanghui Wen, Jinhu Lu, Guanrong Chen
Summary: This paper investigates the distributed optimal consensus problem for second-order multi-agent systems in the presence of system disturbances and cyber attacks. Novel distributed event-triggered controllers are designed to achieve low resource consumption and prevent information leakage. Sufficient conditions are derived to ensure exponential consensus on the optimal solution for all controlled agents.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
