Article
Automation & Control Systems
Zhen Tang, Ziyang Zhen, Zhengen Zhao
Summary: This article addresses the distributed H-8 consensus control problem of general linear multiagent systems with time-varying communication delays and external disturbances. A novel distributed state feedback control protocol is proposed to achieve state consensus over undirected fixed topology while guaranteeing a prescribed disturbance rejection objective. The results show that the proposed approach can accommodate arbitrarily bounded nonuniform time-varying communication delays and has better consensus performance.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Automation & Control Systems
Jingyao Wang, Junfei Qiao, Guanghui Wen, Zhisheng Duan, Tingwen Huang
Summary: This article discusses the rendezvous problem of heterogeneous agents with information transmission delays. It introduces a static protocol based on the damping coefficient, showing that a large damping coefficient can enhance the protocol's robustness. By adapting the damping coefficient using an adaptive approach, two classes of fully distributed and adaptive rendezvous protocols are designed. Numerical simulations are performed to illustrate the analytical results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Filippo Cacace, Alfredo Germani, Costanzo Manes
Summary: This article proposes an improved observer for Lipschitz nonlinear systems with time-varying and known measurement delays, achieving exponential convergence to zero of observation error with any desired decay rate by tuning a gain vector. The delay bound obtained with this observer is less conservative than previous methods, as confirmed by numerical tests. While only one-step observers are considered in this study, a cascade observer can be arranged to handle arbitrarily long delays.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Quan-Yong Fan, Chao Deng, Xiaohua Ge, Cai-Cheng Wang
Summary: This article introduces a method to address the distributed adaptive fault-tolerant control problem for heterogeneous linear multiagent systems with actuator faults and nonuniform time-varying communication delays. The proposed distributed switching observers and adaptive fault-tolerant controllers effectively solve the cooperative fault-tolerant output regulation problem and reduce computational complexity. Illustrative examples demonstrate the validity and efficiency of the developed method in various systems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Ruru Jia, Xiaofeng Zong
Summary: This article investigates time-varying formation control problems of linear multiagent systems with time delays and multiplicative noises under the undirected interactive topology. Sufficient conditions for formation feasibility under unstable and stable formation centers are provided, and it is proven that formation can be achieved for any given time delay and noise intensity. Numerical simulations on a group of unmanned aerial vehicles are used to illustrate the effectiveness of the theoretical results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Chao Ge, Yaxin Zhang, Lei Wang, Yajuan Liu
Summary: This paper investigates an event-triggered transmission scheme for non-fragile networked control systems with probabilistic time-varying delays. A new two-sided Lyapunov-Krasovskii functional is constructed using the sawtooth structure, and sufficient conditions are derived to ensure stability with extended dissipative. A numerical example is provided to demonstrate the effectiveness of the approach.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Information Systems
Keito Inoue, Naoki Hayashi, Shigemasa Takai
Summary: This paper investigates distributed online optimization with dynamic inequality constraints under time-varying communication delays. A group of agents cooperatively estimate an optimal strategy by exchanging sequentially disclosed loss value information. The authors propose a distributed primal-dual algorithm for an enlarged multiagent network with delayed agents, which handles the delayed information. Theoretical analysis shows that the algorithm achieves sublinear bounds for both the dynamic regret and fit functions, even in the presence of communication delays. Numerical examples validate the sublinearity of the proposed method.
Article
Automation & Control Systems
Mengshen Chen, Huaicheng Yan, Hao Zhang, Shiming Chen, Zhichen Li
Summary: This article investigates the consensus problem of linear multiagent systems, introducing an event-triggered mechanism combined with a sampler to utilize network bandwidth and communication energy. Novel criteria for achieving asymptotic consensus under different communication delay cases are obtained, with the demonstration of superiority through a compared example and an application in spacecraft formation flying.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Automation & Control Systems
Yuan Yuan, Yingjie Wang, Lei Guo
Summary: This article investigates a method for the time-varying practical formation problem for spacecrafts subjected to switching topologies and time-delays. It designs a sliding mode observer and formation tracking protocol, and establishes sufficient conditions to ensure the system achieves the goal of time-varying formation with switching topologies. An example is provided to demonstrate the effectiveness of the proposed methodology.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Dinh Cong Huong, Saeid Nahavandi, Hieu Trinh
Summary: This paper addresses the simultaneous estimation problem of event-triggered state and disturbance for Lipschitz nonlinear systems with an unknown time-varying delay. State and disturbance can be robustly estimated using an event-triggered state observer, which only requires the output vector information when an event-triggered condition is met. Unlike previous methods, which assume continuous availability of the output vector information, this approach reduces the stress on communication resources while maintaining acceptable estimation performance. A novel event-triggered state observer is proposed, and a sufficient condition for its existence is established. By introducing algebraic transformations and utilizing inequalities, a convex optimization problem is formulated to derive observer parameters and optimal disturbance attenuation levels. The applicability of the method is demonstrated through numerical examples.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Haik Silm, Rosane Ushirobira, Denis Efimov, Emilia Fridman, Jean-Pierre Richard, Wim Michiels
Summary: The distributed estimation problem for continuous-time observer nodes is addressed in this paper, with a focus on modeling digital communication with variable sampling intervals, transmission delays, and packet dropouts. An LMI for designing observer gains is derived using Halanay's inequality, ensuring exponential stability with a selected convergence rate. A comparison of the maximal delay in a numerical example demonstrates the advantage of a distributed observer over a centralized one.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Yanliang Cui, Juanjuan Ji, Guangtian Shi
Summary: This paper investigates an adaptive event-triggered control for semi-Markovian jump linear systems with process time-varying delays. A switching-mode dependent adaptive event-trigger (AET) is proposed for reducing data transmission amount and involves a positive auxiliary function. A switching state feedback control law is explored using received non-periodical state information. Control design method is conveniently presented using exponential inequality technique.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Mathematics, Interdisciplinary Applications
Fernando E. Serrano, Dibakar Ghosh
Summary: This paper presents a novel controller technique for network synchronization of chaotic systems with time-varying delay. The technique achieves stabilization and synchronization of complex chaotic systems by employing an appropriate Krasovskii-Lyapunov functional and fast switching topology. The controller is designed asynchronously, taking into account the time-varying delays in order to avoid instability and performance degradation of the systems. The study demonstrates that the robust controller considers uncertainties and achieves exact synchronization by switching the action of the controller and the dynamics of the chaotic nodes of the studied systems. Numerical examples on chaotic Rossler systems are provided to validate the theoretical results.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Automation & Control Systems
Dinh Cong Huong
Summary: This paper addresses the problem of event-triggered robust state and fault simultaneous estimation for nonlinear time-delay systems subject to actuator and sensor unknown disturbances. The authors propose a novel event-triggered state observer for the augmented system, which robustly estimates the variable of the original system and the fault. The existence of such an observer is established through a sufficient condition translated into a linear matrix inequality.
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL
(2023)
Article
Computer Science, Information Systems
Peng Wang, Cheng Song, Lu Liu
Summary: This paper investigates the problem of coverage control on a circle with unknown terrain roughness and nonuniform time-varying communication delays. Adaptive control laws are proposed to estimate the roughness function and address nonuniform communication delays. Simulation results demonstrate the effectiveness of the proposed control laws.
SCIENCE CHINA-INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Chang-Ren Zhou, Wei-Wei Che
Summary: This article mainly studies the problem of quantized data-based iterative learning tracking control (QDBILTC) for nonlinear networked control systems in the presence of signals quantization and denial-of-service (DoS) attacks. A corresponding algorithm is proposed to solve this problem, and its effectiveness is demonstrated through digital simulations.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Automation & Control Systems
Xiao-Zheng Jin, Miao-Miao Gao, Wei-Wei Che, Hai Wang
Summary: This article addresses the problem of event-triggered finite-time trajectory tracking control of perturbed Euler-Lagrange systems with nonlinear dynamics and disturbances. It employs the Extreme Learning Machine (ELM) framework and adaptive technique to tackle unknown nonlinearities and mitigate the effects of disturbances, nonlinearities, and errors. An adaptive ELM-based sliding mode control strategy is developed to ensure finite-time convergence of the system. Furthermore, an event-triggered control technique is proposed to regulate control outputs and reduce actuator actions and communication resources. The effectiveness of the strategies is demonstrated through simulations in a robotic manipulator system.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Yong-Sheng Ma, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: This article investigates the problem of observer-based fully distributed containment control for multiagent systems subject to denial-of-service attacks. It establishes a switched fully distributed control framework and develops a novel attack-resilient control scheme to accomplish the containment control task. The major advantages of the devised control scheme are that it does not require any information of the whole network topology structure and only uses information from neighbor agents. Additionally, a novel observer-based attack compensator is designed to resist DoS attacks.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Mechanical
Jiadong Liu, Xiaozheng Jin, Chao Deng, Weiwei Che
Summary: This paper investigates the displacement path-following problem for a class of disturbed cart-pendulum systems under fake data injection (FDI) actuator attacks. A filter operator is proposed to estimate the weight vector caused by unknown attacks and disturbances, enabling parameterization of the actuator attacks using neural networks. Robust path-following control schemes are then proposed, leveraging adaptive neural network and integral sliding-mode techniques, to counteract the impacts of disturbances and FDI attacks. The closed-loop cart-pendulum system with neural network weight estimations and sliding functions achieves uniformly ultimately bounded stability results based on Lyapunov stability theory. Finally, a simulation model of a material robot is employed to validate the proposed control strategy.
Article
Automation & Control Systems
Mouquan Shen, Xianming Wang, Ju H. Park, Yang Yi, Wei-Wei Che
Summary: This article presents a data-driven control method for networked nonlinear systems with event-triggered output. It constructs an improved extended state observer to estimate unknown disturbances and builds an output estimator based on the triggered output and the estimated output. The triggering conditions for different systems are proposed by integrating the estimated disturbances, tracking errors, and actual errors. The effectiveness of the proposed strategies is verified through numerical examples.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Lili Zhang, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: This article investigates the prescribed performance security control problem for nonlinear systems subject to denial-of-service attacks. A security tracking control method is proposed using an attack compensator and a fuzzy estimator to steer the tracking errors to a predetermined neighborhood within a predefined settling time.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Bai-Fan Yue, Wei-Wei Che
Summary: This article studies the dynamic event-triggered fault-tolerant model-free adaptive platooning control problem in vehicle platoon systems subject to sensor faults. A novel redefined output is introduced to assist in proving the synchronous tracking of the position and velocity. The equivalent dynamic linearization technique is used to transform the nonlinear vehicular platooning systems into a linear data model, and an observer is designed to estimate the pseudo-partial derivative parameter and eliminate symbol restriction on it. DET mechanism is introduced to save network resources effectively, and the neural network method is applied to handle sensor faults for safe vehicle driving. A novel DET-based fault-tolerant MFAPC strategy is developed to realize vehicular position and velocity tracking using only input-output data. An example is provided to demonstrate the effectiveness of the designed MFAPC framework.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Civil
Bai-Fan Yue, Wei-Wei Che
Summary: This paper investigates the resilient fault-tolerant model-free adaptive platooning security control issue for the vehicular platooning systems subject to sensor faults and aperiodic denial-of-service attacks. Firstly, an equivalent linear data model is obtained using the partial form dynamic linearization technique. Then, a fault-tolerant control framework is developed with consideration of the sensor faults and a gradient descent method-based neural network is adopted for fault approximation. Thirdly, an attack compensation mechanism is designed and a novel resilient FT-MFAPSC algorithm is proposed for the VPSs against aperiodic DoS attacks, accomplishing the control objectives. Finally, the effectiveness of the developed algorithm is illustrated through simulation examples and comparisons.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Automation & Control Systems
Yong-Sheng Ma, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: This article investigates the problem of model-free adaptive resilient control (MFARC) for nonlinear cyber-physical systems (CPSs) under aperiodic jamming attacks. The MFARC framework is established and an intermediate variable method is introduced to address the issue of unavailable time-varying parameters. A MFARC scheme is devised to track the desired output and solve a feasibility problem, with controller parameters obtained using linear matrix inequality technique. Additionally, a novel attack compensation mechanism is developed to mitigate the impact of aperiodic jamming attacks.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Liang Zhao, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: In this article, the authors study the adaptive fault-tolerant control for multiagent systems under denial-of-service attacks and actuator faults. They propose a novel fault-tolerant control strategy to compensate for node faults and use Lyapunov stability analysis to prove the bounded synchronization of the systems under denial-of-service attacks. The proposed approach is validated through simulation using nonlinear forced pendulum systems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Wei-Wei Che, Lili Zhang, Chao Deng, Zheng-Guang Wu
Summary: The neural network-based adaptive backstepping method is an effective tool for solving the cooperative tracking problem in nonlinear multiagent systems (MASs). However, it cannot be directly applied to cases without continuous communication due to discontinuous signals caused by the absence of continuous communication. To address this issue, a hierarchical design scheme involving distributed cooperative estimators and neural network-based decentralized tracking controllers is proposed. The proposed method uses dynamic event-triggered mechanism to estimate unknown parameters and design a backstepping-based decentralized neural network tracking controller, achieving asymptotic tracking and bounded signals in the closed-loop systems.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Computer Science, Artificial Intelligence
Chao Deng, Xiao-Zheng Jin, Zheng-Guang Wu, Wei-Wei Che
Summary: In this article, a hierarchical cooperative resilient learning method is introduced to solve the cooperative tracking problem for a class of nonlinear multiagent systems (MASs) with unknown dynamics under denial-of-service (DoS) attacks. A resilient model-free adaptive control (MFAC) algorithm is developed to withstand the influence of communication delays and DoS attacks. Simulation results show the effectiveness of the developed method.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Xinyao Li, Ying Zou, Chao Deng
Summary: This work explores the development of a backstepping-based adaptive control method for nonlinear fractional-order systems with systematic uncertainties, time-varying external disturbances, and quantized control input. A novel analog chain rule computation method is proposed to handle the fractional derivatives of composite functions encountered in the backstepping procedure. A quantified adaptive controller is designed to guarantee system stability and convergence of the tracking error using the direct fractional Lyapunov method. Simulated studies confirm the effectiveness of the control strategy.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Civil
Yong-Sheng Ma, Wei-Wei Che, Chao Deng, Zheng-Guang Wu
Summary: This article investigates the problem of data-driven distributed vehicle platoon control for heterogeneous nonlinear vehicle systems. The systems are transformed into linear data models using the increment form, and a novel data-driven distributed cooperative controller is proposed to achieve the platoon control objective. The stability analysis problem is converted into a feasibility problem using the linear matrix inequality technique. The main advantage of the proposed control algorithm is its reliance on only the position and speed information of neighboring vehicles, without requiring any pre-training process. Simulation results demonstrate the effectiveness of the devised control algorithm through comparisons.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
