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Observer-Based Leader-Following Secure Consensus for Multi-Agent Systems with Nonlinear Dynamics and External Disturbance Under Denial of Service Attacks 5

Observer-Based Leader-Following Secure Consensus for Multi-A...

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5th International Conference on Artificial Intelligence and Computer engineering, ICAICE 2024

作者： Hu, Liduo Zhang, Wei Hu, Zhi Cai, Yuhang Shanghai University of Engineering Science Laboratory of Intelligent Control and Robotics Shanghai China

ISBN: (纸本)9798331528911

This paper introduces an Unknown Input Observer (UIO) for nonlinear systems with One-Sided Lipschitz (OSL) and Quadratic Inner-Boundedness (QIB) properties. The UIO enables unknown input reconstruction and state estimation. Besides the UIO show resilience against Denial of Service (DoS) attacks that can disrupt multi-agent communication. To counteract these attacks, the system uses buffer units to retain real-time data, allowing agents to access the latest states during disruptions. We present a control protocol that facilitates leader-follower consensus under simultaneous DoS attacks, detailing the upper limits on their frequency and duration. Numerical simulations demonstrate the approach's effectiveness. © 2024 IEEE.

关键词： Denial-of-service attack

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Aggressive and robust low-level control and trajectory tracking for quadrotors with deep reinforcement learning

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Neural Computing and Applications 2025年第3期37卷 1223-1240页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Department of Control Science and Engineering Harbin Institute of Technology Shenzhen Shenzhen518055 China Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen518055 China

Executing accurate trajectory tracking tasks using a high-performance low-level controller is crucial for quadrotors to be applied in various scenarios, especially those involving uncertain disturbances. However, due to the uncertainties in disturbed environments, developing effective low-level controllers with traditional model-based control schemes is challenging. This paper presents an aggressive and robust reinforcement learning (RL)-based low-level control policy for quadrotors. The policy maps the observed quadrotor state directly to motor thrust commands, without requiring the quadrotor dynamics. Additionally, a trajectory generation pipeline is developed to improve the accuracy of trajectory tracking tasks based on differential flatness. With the learned low-level control policy, extensive simulations and real-world experiments are implemented to validate the performance of the policy. The results indicate that our RL-based low-level control policy outperforms traditional proportional–integral–derivative (PID) control methods and related learning-based policies in terms of accuracy and robustness, particularly in environments with uncertain disturbances. Furthermore, the proposed RL-based control policy exhibits an aggressive response in trajectory tracking, even when the speed of the desired trajectory is increased to 6 m/s. Moreover, the learned policy demonstrates strong vibration suppression capabilities and enables the quadrotor to recover to a hovering state from random initial conditions with shorter response time. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Deep reinforcement learning

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Time-Varying Formation Tracking control of Heterogeneous Multi-Agent Systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai Research Institute for Intelligent Autonomous Systems Tongji University the National Key Laboratory of Autonomous Intelligent Unmanned Systems the Frontiers Science Center for Intelligent Autonomous System of Ministry of Education the College of Electronic and Information Engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and Engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems control theory Autonomous systems Stability

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All-Fabric Bi-directional Actuators for Multi-joint Assistance of Upper Limb

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Journal of Bionic engineering 2023年第6期20卷 2661-2669页

作者： Junlin Ma Diansheng Chen Zhe Liu Jie Wei Xianglin Zhang Zihan Zeng Yongkang Jiang Institute of Robotics Beihang UniversityBeijing100191China Department of Control Science and Engineering Tongji UniversityShanghai201804China Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210China

According to clinical studies,upper limb robotic suits are vital to reduce therapist fatigue and accelerate patient *** pneumatic actuators have drawn increasing attention for the development of wearable robots due to their low weight,flexibility,and high power-to-weight ***,most of current actuators were designed for the flexion assistance of a specific joint,and that for joint extension requires further ***,designing an actuator for diverse working scenarios remains a *** this paper,we propose an all-fabric bi-directional actuator to assist the flexion and extension of the elbow,wrist,and fingers.A mathematical model is presented that predicts the deformation and guides the design of the proposed bi-directional *** further validate the applicability and adaptability of the proposed actuator for different joints,we developed a 3-DOF soft robotic *** results show that the robotic suit can assist the motion of the elbow,wrist,and finger of the subject.

关键词： Soft robotic suits Fabric-based actuators Multi-DOF motion Upper limb rehabilitation

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Distributed Optimization and Scaling Design for Solving Sylvester Equations

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Journal of Systems science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

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Indirect adaptive admittance control based on position synchronization of robot-assisted nasopharyngeal surgery 2

Indirect adaptive admittance control based on position synch...

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2nd International Conference on Electrical, Electronics, and Information engineering, EEIE 2023

作者： Hu, Zhi Liu, Yueling Song, Aiguo School of Instrument Science and Engineering Southeast University Nanjing China Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9781510672840

In the surgery of nasopharyngeal cancer, the surgeon operates through natural channels within small room. In its robot-assisted surgery, collisions between two manipulators and parameter variation of local tissue may lead to contact force change, It may cause target position offset. As the vessels and nerves were distributed densely in head and neck. The control system needs to ensure the operating contact force is within the safety threshold. It can avoid soft tissue tearing caused by changing of relative position over the limits. The research studies indirect adaptive admittance control based on position synchronization, which adjust the damping compensation rate. It improves the force control precision and system robustness of robot-assisted surgery through alleviating the effect of stiffness variation and collisions. And it can improve surgery security. © 2024 SPIE.

关键词： Compliance control

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Interval analysis for neural networks with application to fault detection

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science China(Information sciences) 2024年第11期67卷 222-237页

作者： Zhenhua WANG Youdao MA Song ZHU Thach Ngoc DINH Yi SHEN Department of Control Science and Engineering Harbin Institute of Technology National Key Laboratory of Complex System Control and Intelligent Agent Cooperation School of Mathematics China University of Mining and Technology The CEDRIC-Lab Conservatoire National des Arts et Métiers (CNAM)

This paper investigates an interval analysis method for neural networks and applies it to fault detection for systems with unknown but bounded measurement noise. First, a novel interval analysis method is presented, which can compute the bounds of the output of a feedforward neural network subject to a bounded input. By applying the proposed interval analysis method to a network trained with fault-free system data, adaptive thresholds for fault detection are computed. Finally, one can acquire fault detection results via a fault detection strategy. The proposed method can achieve tight bounds of the network output and employ simple operations, which leads to accurate fault detection results and a low computational burden.A numerical simulation and an experiment on an AC servo motor are given to illustrate the effectiveness and superiority of the proposed method.

关键词： interval analysis feedforward neural network fault detection adaptive thresholds

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A zeroth-order algorithm for distributed optimization with stochastic stripe observations

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science China(Information sciences) 2023年第9期66卷 297-298页

作者： Yinghui WANG Xianlin ZENG Wenxiao ZHAO Yiguang HONG School of Automation and Electrical Engineering University of Science and Technology Beijing Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Department of Control Science and Engineering Tongji University

Recent years have seen a rising interest in distributed optimization problems because of their widespread applications in power grids, multi-robot control, and regression *** the last few decades, many distributed algorithms have been developed for tackling distributed optimization problems. In these algorithms, agents over the network only have access to their own local functions and exchange information with their neighbors.

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Managing Battery Performance Degradation Using Physics-Informed Learning Scheme for Multiple Health Indicators

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7309-7321页

作者： Qin, Linxiao Sun, Tao Sun, Xi-Ming Xia, Weiguo Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Tsinghua University Department of Automation Beijing100084 China

To address the challenges in battery health management, this paper introduces a physics-informed neural network predictor-estimator scheme. In the framework, the predictor forecasts health degradation, setting benchmarks for the estimator, while the estimator provides calibrations for the predictor as substitution to infeasible measurement techniques. For the predictor design, a linear-exponential model is employed for two-stage degradation prediction, enabling online parameter updates and knee point detection. For the estimator design, three neural networks embedded with Coulomb counting and equivalent circuits are proposed to estimate state of charge, internal resistance, and capacity, respectively. Experimental results on the A123 dataset demonstrate superior accuracy of our scheme, with a maximum R-squared improvement of 22.8% in prediction tasks and 11.5% in estimation tasks, while maintaining lightweight network structures with fewer than 1000 floating point operations and 200 parameters. © 2015 IEEE.

关键词： Electronic health record

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A Fuzzy Fusion Approach for the Prediction of Position and Orientation in Robot-Assisted Cardiovascular Surgery 5

A Fuzzy Fusion Approach for the Prediction of Position and O...

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5th International Conference on robotics and Computer Vision, ICRCV 2023

作者： Hu, Zhi Sun, Liyan Song, Aiguo School of Instrument Science and Engineering Southeast University Nanjing China Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai China

ISBN: (纸本)9798350326369

To assist doctors in cardiovascular intervention, the use of robots in surgery can effectively separate interventionalists from X-ray radiation, prevent the spread of respiratory diseases, perform remote operations to alleviate the regional imbalance of medical resources and address some procedural challenges. However, a lack of force feedback in human computer interaction of current surgical robots affects surgical efficiency and safety. In cardiovascular surgery, the catheter bends and twists as it is the dynamic multipoint line contact with the vessel. It is difficult to accurately model and register it. In addition, time delay affects system transparency. This paper proposes a multi-information fuzzy fusion approach that is based on medical experience in order to predict position and orientation online. More specifically, Fitts law is developed with a two-motion collaborative to estimate the surgical movement time. Experimental results reveal that the proposed method can result in high system transparency in robot-assisted cardiovascular surgery. It could further improve accuracy and security in surgical procedures. © 2023 IEEE.

关键词： Forecasting

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