Article
Automation & Control Systems
Runhan Zhang, Yuanyuan Zhang, Xiaofeng Zong
Summary: This paper investigates the stochastic leader-following consensus problem of discrete-time nonlinear multi-agent systems (MASs) with multiplicative noises. Parameter-dependent Lyapunov functions are constructed for the analysis of consensus control of first-order and second-order MASs. Scalar inequalities for control gains, intensity of multiplicative noises, and the Lipschitz constant are established as sufficient conditions for achieving mean square and almost sure leader-following consensus.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Automation & Control Systems
Kairui Chen, Chuance Yan, Qijun Ren, Junwei Wang
Summary: This paper investigates leader-following consensus problem for nonlinear multi-agent systems with measurement noises under fixed and Markovian switching topologies. A dynamic event-triggered consensus protocol is designed to alleviate the utilization of communication and computation resources, with the coupling strength restricted in a given interval. Stochastic stability theorem is used to prove the achievement of leader-following consensus under fixed topology, with an estimation of the convergence rate. Moreover, the problem is studied under switching topologies subjecting to the Markovian process, which is applicable to practical situations with a time-varying communication environment. Simulation examples are given to validate the proposed results.
IET CONTROL THEORY AND APPLICATIONS
(2023)
Article
Mathematics, Applied
Arumugam Parivallal, Yoon Mo Jung, Sangwoon Yun
Summary: This article aims to analyze the leader-following consensus for multi-agent systems (MASs) in the presence of cooperative and competitive interactions. The primary aim of this article is to design a hybrid-triggered control protocol that ensures the bipartite leader-following consensus of MASs under controller gain variations.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2023)
Article
Automation & Control Systems
Wenfeng Hu, Yi Cheng, Chunhua Yang
Summary: In this work, a novel reset consensus protocol with a time-varying gain matrix is developed to address the leader-following consensus problem of multi-agent systems. The protocol integrates a high-dimensional element through reset actions triggered by a prescribed reset band, which distinguishes it from existing results. By converting the original closed-loop system to an equivalent linear time-varying system, the time-varying system approach for linear multi-agent systems over fixed/switching networks is developed. The proposed reset consensus protocol is found to improve the transient performance. Numerical examples are provided to illustrate the theoretical results and effectiveness. (c) 2022 Elsevier Ltd. All rights reserved.
Article
Automation & Control Systems
Yi Cheng, Wenfeng Hu, Yuqian Guo, Yongfang Xie
Summary: This paper investigates the leader-following consensus problem of linear multi-agent systems over directed communication graphs, proposing a novel distributed reset proportional-integral consensus controller. Through a hybrid system analysis approach and a novel Lyapunov function, the conditions for achieving consensus are obtained, further demonstrating the controller's ability to improve transient performance.
Article
Computer Science, Interdisciplinary Applications
Wang Li, Haifeng Dai, Lingzhi Zhao, Donghua Zhao, Yongzheng Sun
Summary: In this paper, the influence of noise on the consensus of leader-following multi-agent systems is explored. Conditions for achieving consensus in the presence of noise are obtained using algebraic graph theory and stability theory of stochastic differential equations. The results reveal the positive role of noise in the emergence of consensus. Numerical simulations are provided to demonstrate the analytical results.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Computer Science, Information Systems
Guilu Li, Chang-E Ren, C. L. Philip Chen
Summary: This paper investigates the preview-based leader-following consensus control of distributed multi-agent systems with a directed acyclic graph. By utilizing state augmentation technique and preview control method, the consensus control problem is transformed into finite horizon and infinite horizon LQR problems to ensure asymptotic consensus of the system. The simulation results demonstrate the effectiveness of the distributed leader-following consensus controller designed in this paper.
INFORMATION SCIENCES
(2021)
Article
Chemistry, Multidisciplinary
Siheng Zong, Yu-Ping Tian
Summary: This paper investigates the consensus problem of multi-agent systems with increasing communication distances, modeling the system using a time-delay system. It is proven that under certain topological conditions, the system can achieve consensus, and the growth rate of the maximum delay is negatively correlated with the rate of achieving consensus.
APPLIED SCIENCES-BASEL
(2021)
Article
Mathematics, Applied
Shanshan Gao, Shenggui Zhang, Xinzhuang Chen, Xiaodi Song
Summary: For a first-order leader-follower multi-agent system with a directed graph, the consensus convergence rate is determined by the algebraic connectivity. Adding arcs to the followers can improve the consensus convergence rate. This paper investigates the effects of adding arcs to the strongly connected followers' interaction topology on the algebraic connectivity.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Automation & Control Systems
Mohammad Javad Mirzaei, Sehraneh Ghaemi, Mohammad Ali Badamchizadeh, Mahdi Baradarannia
Summary: In this paper, a robust distributed consensus control method based on adaptive time-varying gains is proposed for nonlinear multi-agent systems (MAS) with uncertain parameters and external disturbances. The discontinuous and continuous adaptive integral sliding mode control strategies are designed to achieve precise consensus for non-identical MASs influenced by perturbations. An adaptive scheme is used to overcome the unknown upper bound of perturbations. The designed distributed super-twisting sliding mode strategy adjusts the gain of the control inputs and guarantees the proper performance of the protocol without chattering phenomenon. Simulation results demonstrate the robustness, accuracy, and effectiveness of the proposed methods.
Article
Engineering, Multidisciplinary
Peng Zhang, Quanbao Wang, Yueying Wang, Jiwei Tang, Dengping Duan
Summary: This technical note investigates the agent-based finite-time leader-following consensus for Earth-observation systems with multiple stratosphere airships. The study considers the high-order nonlinear dynamic and external disturbances in multi-agent systems. By using a distributed observer to acquire the state of the leader airship, a dynamic cascade control is designed to achieve finite-time leader-following consensus for Earth-observation systems. Mathematical proofs demonstrate the finite convergence of the stratosphere airship earth-observation system, and simulation results confirm the effectiveness of the proposed scheme.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Mathematics, Applied
Boyu Wang, Yijun Zhang, Miao Wei
Summary: This article investigates the intermittent-based fixed-time (IBFT) consensus problem for nonlinear multi-agent systems. By designing a novel IBFT control protocol, the follower agents can achieve consensus with the leader's state within a fixed time. A new differential inequality is proposed to analyze the IBFT stability and ensure the fixed-time (FT) consensus of the nonlinear systems. The results are extended to the directed communication situation among agents.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Engineering, Multidisciplinary
Haoyue Yang, Hao Zhang, Zhuping Wang, Huaicheng Yan
Summary: This paper focuses on the leader-following reliable consensus control problem of a class of discrete-time semi-Markovian jump multi-agent systems. It proposes control protocols and methods based on stochastic jump processes to characterize system parameter changes and actuator faults. The presented results are verified through two examples.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Jie Ren, Qiang Song, Yanbo Gao, Min Zhao, Guoping Lu
Summary: This paper investigates the leader-following consensus problem for a singular multi-agent system with nonlinear dynamics and signed digraph topology. An algorithm is proposed to address the structural balance problem of the signed network, suitable for all types of signed graphs. Consensus conditions are established using M-matrix theory for the singular nonlinear multi-agent system, with global asymptotic stability conditions presented for structurally unbalanced signed networks.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
(2021)
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
Long Cheng, Ang Wang, Shijie Qin
Summary: This article proposes the idea of using fuzzy model predictive control approach for high-precision positioning and designs a prototype of the stick-slip type piezoelectric actuator. By establishing a fuzzy model for the entire SSPEA, a simplified predictive controller can be designed. Experimental results demonstrate satisfactory control performance.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2023)
Article
Robotics
Zhengwei Li, Long Cheng, Zeyu Liu
Summary: This article reports an intentional blocking based photoelectric pressure sensor that has high sensitivity, large pressure-sensing range, superior stability, and high signal-to-noise ratio. It can be used for detecting subtle collisions and for applications in music playing and object weighing when integrated into a tactile glove.
Article
Automation & Control Systems
Ran Cao, Long Cheng
Summary: This article investigates the distributed dynamic event-triggered control of networked Euler-Lagrange systems with unknown parameters. By utilizing the designed control algorithm, the leaderless consensus problem and containment problem are solved, and the estimations of unknown parameters are updated with an adaptive updating law. Simulation results show that the proposed method can increase the average lengths of event intervals and does not affect the time of achieving consensus/containment and the steady-state control performance.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Electrical & Electronic
Yifa Liu, Long Cheng
Summary: This study proposes an extremely stealthy attack strategy that can make the system residual almost always unchanged, thereby invalidating both the widely used ?(2) detector and the advanced summation detector and eventually causing unbound state deviations. Compared with existing attack methods, the proposed strategy can reduce the sum of cumulative residual increments by 85.39% while causing 9817001 times of state deviations in numerical simulations.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Jiantao Yang, Tairen Sun, Long Cheng, Zeng-Guang Hou
Summary: This article introduces a novel spatial repetitive impedance learning control strategy to enhance interaction performance in robot-assisted rehabilitation and leg exoskeletons. By exploiting the spatial periodicity characteristics of the desired trajectory and human impedance, the proposed control approach enables the human-robot system to complete a repetitive task with unspecified speeds according to the users' strengths and motion capacity.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2023)
Article
Computer Science, Artificial Intelligence
Tiandong Zhang, Rui Wang, Shuo Wang, Yu Wang, Long Cheng, Gang Zheng, Min Tan
Summary: This article presents a method for the autonomous skill learning of water polo ball heading for a robotic fish in highly dynamic aquatic environments. A novel MSPCL framework is proposed to cope with the complex tasks, which includes curriculum scheduler, difficulty criterion, serial-parallel curriculum generation, and performance measure modules. The soft actor-critic algorithm is utilized for training the policy network. Comparative simulations and swimming pool experiments are carried out to verify the effectiveness and robustness of the proposed method.
IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS
(2023)
Article
Robotics
Haoyu Zhang, Long Cheng, Yu Zhang
Summary: This letter proposes a robust stochastic differential equation approach for learning point-to-point motions in an adversarial way. The proposed stochastic dynamical model combines the advantages of the stochastic differential equation and the transformer-like function together to achieve both robustness and accuracy of the learning. The adversarial training method is proposed to simplify the way of updating the parameters of the model. The state of the proposed stochastic dynamical system is mathematically proved to converge asymptotically in the mean square sense, and it has been experimentally validated on the LASA dataset and by the trajectory-programming task of the Franka Emika robot. The experimental results show that: (1) the adversarial training method helps the model to achieve higher reproduction accuracy; (2) the trajectories generated by the proposed model achieve higher accuracy in both the noise-free condition (by approximately 14.9%) and the noisy condition (by approximately 17.8%) compared with the state-of-the-art methods in terms of the similarity to the demonstration; and (3) the proposed approach can learn smoother trajectories even if the observations are contaminated by noises.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Engineering, Biomedical
Yongxiang Zou, Long Cheng, Lijun Han
Summary: This paper proposes an adversarial autoencoder model, SGMD-AAE, to address the problem of incomplete sEMG signals caused by interferences during data measurement. The model includes a self-mask generator and a multi-view discriminator, enhancing the reconstruction ability of sEMG signals by introducing adversarial loss and extracting deep features from both time and frequency domains. Experimental results on a benchmark database and a self-collected dataset demonstrate the superiority of the SGMD-AAE model in reducing NRMSE and increasing PSNR, as well as achieving high recognition accuracy for hand gesture recognition even in extreme cases where most of the sEMG signals are missing.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Zeyu Liu, Long Cheng, Zhengwei Li
Summary: Wrist pulse is a valuable source of information about human beings and can be used for disease diagnosis. A high-quality wrist pulse measurement system based on a pressure sensor is proposed in this study. The system has a high signal-to-noise ratio and the ability to resist environmental interference. The measured wrist pulse data are applied in emotion classification, achieving good accuracy.
IEEE SENSORS JOURNAL
(2023)
Article
Computer Science, Artificial Intelligence
Ding Wang, Mingming Ha, Long Cheng
Summary: In this article, a novel neuro-optimal tracking control approach is developed for discrete-time nonlinear systems. By constructing an augmented plant and using a value-iteration algorithm, the trajectory tracking design and uniformly ultimately bounded stability of the closed-loop system are achieved.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Robotics
Zhuoliang Zhang, Chao Zhou, Long Cheng, Xiaofei Wang, Min Tan
Summary: This article introduces the development of an artificial lateral line (ALL) sensor inspired by fish sensory organs, which is used to measure the flow velocity of robotic fish. The sensor senses the local flow field by measuring the deformation of the sensitive element. A fairing structure is proposed to suppress turbulence noise and yaw motion noise caused by fishlike oscillation of the tail. The proposed ALL array system, combined with a kinematic-based fusion method, achieves a mean absolute error of 0.018 m/s, a linearity (R2) of 0.951, and a position tracking error of 0.085 m. Additionally, the fairing structure improves the signal-to-noise ratio by 116%.
IEEE TRANSACTIONS ON ROBOTICS
(2023)
Article
Engineering, Biomedical
Ning Sun, Long Cheng, Xiuze Xia, Lijun Han
Summary: This paper proposes a new index finger exoskeleton with semi-wrapped fixtures and elastomer-based clutched series elastic actuators. The semi-wrapped fixture improves convenience and connection stability, while the elastomer-based clutched actuator enhances passive safety. The exoskeleton mechanism is analyzed and optimized to minimize force along the phalanx.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Yongxiang Zou, Long Cheng, Lijun Han, Zhengwei Li, Luping Song
Summary: This letter proposes a novel MLHG model to improve the robustness of sEMG-based hand gesture recognition, using multiple labels to decode the sEMG signals from two perspectives. The MLHG model achieves an accuracy of 99.26% for within-session hand gesture recognition, 78.47% for cross-time, and 53.52% for cross-subject.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Automation & Control Systems
Ruichen Ma, Yu Wang, Shuo Wang, Long Cheng, Rui Wang, Min Tan
Summary: This paper proposes a learning-based path following control scheme for a biomimetic underwater vehicle (BUV) driven by undulatory fins. A dynamic line-of-sight (DLOS) guidance system is designed to detect the reference path. A deep reinforcement learning (DRL) algorithm, sample-observed soft actor-critic (SOSAC), is proposed to train the control policy. The experiments show that our BUV can achieve path following control in an indoor pool environment using this control scheme.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Yaming Ou, Junfeng Fan, Chao Zhou, Shifei Tian, Long Cheng, Min Tan
Summary: In this article, an underwater active vision measurement system based on binocular structured light is designed for high-precision 3-D reconstruction. Fusion technology of binocular camera and laser addresses underwater optical attenuation and feature sparsity. A laser scanner based on the mirror galvanometer is used for static scanning, and underwater refraction models are proposed. A new laser-based calibration algorithm is also proposed. The effectiveness of the system is verified by analyzing the 3-D reconstruction results.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
