Article
Computer Science, Information Systems
Siyang Zhao, Jinyong Yu
Summary: This paper introduces a co-design approach for fault detection and time-varying formation control for nonlinear leader-following multi-agent systems. The proposed approach utilizes relative output information to develop fault detection observers that can detect multiple faulty agents simultaneously. Precise identification of potential faulty agents is achieved through evaluating the residual signal and logical reasoning.
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Junmin Peng, Jianbo Li, Kaining Wang, Shenping Xiao, Chaoyong Li
Summary: This paper studies the prescribed performance control problem of multiple parametric strict feedback systems under switching digraphs, and proposes an adaptive distributed control algorithm to handle unknown disturbances and unknown parameters. By employing command filtered technique, the issue of complex derivation in backstepping control is overcome.
SYSTEMS & CONTROL LETTERS
(2023)
Article
Automation & Control Systems
Jun Huang, Qingyuan Li, Xudong Zhao, Min Zhang, Yueyuan Zhang
Summary: This article discusses the consensus problem of nonlinear multi-agent systems with incremental quadratic constraints and semi-Markov switching topology. In order to simulate the delay of the communication network, the nonlinear function containing the delay term is considered, and the control protocol is designed based on the dynamics of adjacent agent states and desired agent states. By utilizing the characteristics of the Kronecker product, the distributed system is converted to a centralized system. The effectiveness of the control protocol is demonstrated through numerical simulations.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Information Systems
Wei Cao, Jinjie Qiao, Ming Sun
Summary: A distributed iterative learning control protocol is proposed for state consensus tracking of a singular multi-agent system, utilizing singular value decomposition and switching topology graph to divide and track system states. The proposed algorithm demonstrates convergence and the ability to approach the desired state gradually with an increase in iterations.
Article
Computer Science, Information Systems
Chunping Wang, Jiaqi Wang, Ping Wu, Jinfeng Gao
Summary: This research discusses the cooperative control problem of discrete-time multi-agent systems (MASs) considering bounded uncertain time-delays and directed switching topologies. By applying model transformations and matrix theory, an augmented system method is introduced to handle a heterogeneous time-delay MAS. The convergence issue of the product of innumerable row stochastic matrices is then addressed to solve the consensus problem. Sufficient conditions for asymptotic consensus of the system under directed switching topologies are obtained. Furthermore, a novel consensus-based formation control strategy is designed for the formation control of a second-order differential robot system, providing sufficient and necessary conditions. The effectiveness of the obtained results is verified through simulations.
Article
Automation & Control Systems
Ronghu Chi, Yangchun Wei, Rongrong Wang, Zhongsheng Hou
Summary: This study proposes an observer-based iterative learning control method for accurate consensus tracking in nonlinear nonaffine multi-agent systems. By estimating the uncertainty of nonrepetitive initial states and disturbances and utilizing I/O data, it aims to reduce the influence of nonrepetitive initial values and measurement noises in iterative learning control.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Automation & Control Systems
Cun Wang, Zupeng Zhou, Xisheng Dai, Xufeng Liu
Summary: This paper investigates the consensus tracking problem for linear and nonlinear partial difference multi-agent systems with switching communication topology and control delay. A discrete distributed consensus protocol with initial value learning is designed for each agent using relative local measurements of neighboring followers, considering spatio-temporal discretization and initial state deviation, by employing a D-type iterative learning approach. The necessary and sufficient conditions are obtained through rigorous mathematical analysis, ensuring solvability of the consensus tracking control of the MASs under the switching of the communication topology. After applying the designed protocol, the consensus tracking error between any two agents can converge to zero in terms of the L2 norm and along the positive direction of the iteration axis. Finally, simulation examples are presented to validate the effectiveness of the protocol and theoretical results.
Article
Mathematics
Xiaoya Chen, Huiying Chen
Summary: This study investigates the problem of time-varying formation tracking (TVFT) control using event-triggered and switching topological mechanisms. The TVFT is evaluated through consensus analysis and deduced using linear matrix inequality techniques combined with Lyapunov stability theory. Two cases of TVFT compensational signals are presented to enhance the algorithm's applicability. The effectiveness of the theoretical analysis is demonstrated through 3D figures and comparison tables.
Article
Engineering, Electrical & Electronic
Guoliang Zhu, Kexin Liu, Haibo Gu, Weilin Luo, Jinhu Lu
Summary: This paper investigates the formation control problem for linear multi-agent systems under switching directed topologies and proposes two distributed observer-based event-triggered control schemes. The boundedness of formation errors and avoidance of Zeno behaviors are guaranteed by both schemes, which are verified by simulations and experiments.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2022)
Article
Automation & Control Systems
Yizhou Lu, Xiwang Dong, Qingdong Li, Jinhu Lv, Zhang Ren
Summary: This paper investigates the time-varying group formation tracking problems for general linear multi-agent systems with unknown control input and switching topologies. By adjusting the properties in the Laplacian matrix and introducing control protocols based on neighboring interaction relationships, the influence of unknown control input from leaders can be handled and information can be effectively delivered to achieve the expected formations.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Jing Wu, Xisheng Dai, Senping Tian, Qingnan Huang
Summary: This paper studies the consensus control of nonlinear impulsive distributed parameter multi-agent systems (IDPMASs) that behave dynamically with respect to time and space. It proposes a distributed P-type iterative learning consensus control protocol for achieving complete consensus in nonlinear parabolic IDPMAS, considering network topologies information and nearest neighbor knowledge. The convergence analysis of consensus errors is rigorously provided using impulsive Gronwall inequality and mild solution formula, along with established convergence conditions. Furthermore, the consensus control of nonlinear second-order hyperbolic IDPMAS is investigated using an open-closed-loop P-type consensus control protocol, which considers both current and last iterative consensus errors. The theoretical result demonstrates the convergence of consensus errors between any two agents to 0 with increasing iterations under given conditions. Two numerical simulations are provided to demonstrate the effectiveness of the proposed methods.
EUROPEAN JOURNAL OF CONTROL
(2023)
Article
Automation & Control Systems
Shuang Liang, Fuyong Wang, Zengqiang Chen, Zhongxin Liu
Summary: This article investigates the formation control problem for a class of discrete-time heterogeneous multi-agent systems. A novel formation control protocol is proposed by utilizing relative local information and desired formation information. Sufficient conditions for reaching the desired formation are derived for the discrete-time heterogeneous multi-agent systems, and necessary and sufficient conditions are also obtained when the system has the same number of first-order and second-order agents. The feasibility of the obtained results is demonstrated through numerical examples.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Automation & Control Systems
Furqan Memon, Cheng Shao
Summary: This paper presents a model-free PID type iterative learning control approach for nonlinear batch processes, using dynamic linearisation and quadratic performance index to optimize PID controller parameters, and discusses the convergence analysis of the optimal PID type DDILC. Simulation examples demonstrate the effectiveness of the proposed scheme.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
Article
Engineering, Electrical & Electronic
Zhichen Li, Yu Zhao, Huaicheng Yan, Hao Zhang, Lu Zeng, Xiaolei Wang
Summary: This paper investigates the time-varying formation tracking control problem for multi-agent systems (MASs). The main objective is to achieve asymptotic convergence of formation tracking error despite nonparametric and nonvanishing uncertainties. A fuzzy extended state observer (FESO) based on event-triggered mechanism is proposed to estimate unmodeled dynamics and external disturbances. Furthermore, a distributed control law is developed using neighborhood formation tracking errors, and total disturbance compensation is introduced to attenuate uncertainty influence in real time. The effectiveness of the proposed control protocol is demonstrated using a numerical example on unmanned aerial vehicle swarm system.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Computer Science, Information Systems
Xiangli Jiang, Guihua Xia, Zhiguang Feng, Zhengyi Jiang
Summary: This paper investigates the consensus tracking of singular multi-agent systems with Lipschitz-type nonlinearities and exogenous disturbances. By utilizing algebraic graph theory and linear matrix inequality technique, tracking consistency is first regulated in the concerned MAS under completely known transition probabilities, then extended to partially known probabilities. The theoretical analysis is validated by numerical examples.
INFORMATION SCIENCES
(2021)
