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controllability of heterogeneous networked sampled-data systems

Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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A Review of Wind Turbine Blade Morphing:Power,Vibration,and Noise

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Fluid Dynamics & Materials Processing 2025年第4期21卷 657-695页

作者： Md.Mahbub Alam Center for Turbulence Control School of Mechanical Engineering and AutomationHarbin Institute of Technology(Shenzhen)Shenzhen518055China

Wind turbines play a vital role in renewable energy *** review examines advancements in wind turbine blade morphing technologies aimed at enhancing power coefficients,reducing vibrations,andminimizing noise ***,vibration,and noise levels can be optimized through morphing techniques applied to the blade’s shape,leading edge,trailing edge,and ***-edge morphing is particularly effective in improving efficiency and reducing noise,as flow attachment and separation at the leading edge significantly influence lift and vortex *** technologies often draw inspiration from bionic designs based on natural phenomena,highlighting the potential of biomimicry to improve aerodynamic performance and energy *** fluid-structure interactions is critical to ensuring the lifespan,performance,and safety of wind turbine blades,which directly affect operational efficiency and noise *** review underscores the importance of comprehending the interdependencies between aerodynamics,vibration,and noise to guide future research and policy in sustainable wind energy *** summarizing key advancements in the field,this paper serves as a valuable resource for researchers,policymakers,and industry leaders involved in wind energy technologies.

关键词： Wind turbine blade morphing efficiency vibration noise bionic renewable energy

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 206-217页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical Engineering Applied Mechanics LaboratoryDepartment of Engineering MechanicsTsinghua UniversityBeijing 100084China Institute of Nuclear and New Energy Technology Tsinghua UniversityBeijing 100084China Shanghai Aerospace Control Technology Institute Shanghai 201109China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai 201109China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common *** from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific ***,we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement *** exploit collective milling structures of natural herds to cage the targets,and adopt a switching control policy inspired by sperms’chiral dynamics to optimize the trajectories of individuals,through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical,adaptive and scalable *** exists a critical swarm size,beyond which the excessive competition between agents would generate large mechanical forces,leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple *** work provides physical insights into distributed active swarms and could offer a multilevel,decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices,machine immunity,and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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Observer-Based Multi-Agent Reinforcement Learning for Pursuit-Evasion Game With Multiple Unknown Uncertainties

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IEEE Transactions on automation Science and engineering 2025年 22卷 14332-14345页

作者： Liu, Yangyang Liu, Chun Meng, Yizhen Jiang, Bin Wang, Xiaofan Shanghai University School of Mechatronic Engineering and Automation Shanghai200444 China Shanghai University School of Mechatronic Engineering and Automation Institute of Artificial Intelligence Shanghai200444 China Shanghai Aerospace Control Technology Institute National Key Laboratory of Space Target Awareness Shanghai China Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai201109 China Nanjing University of Aeronautics and Astronautics College of Automation Engineering Nanjing210016 China Shanghai Institute of Technology Shanghai201418 China

This paper aims to investigate the challenging problem of a multi-agent game with multiple pursuers and a single evader in an environment with multiple unknown uncertainties. A coupled approach combining decentralized observers and reinforcement learning (RL) controllers is proposed to deal with this scenario. Firstly, decentralized observers driven by auxiliary control laws are introduced to estimate the states of uncertain systems, with their best responses obtained through the adaptive dynamic programming (ADP) method. The estimated states, which reflect the actual states of the pursuers’ systems, are concurrently transmitted to the RL controllers. Subsequently, the controllers are trained with observer-based heterogeneous-agent proximal policy optimization (OHAPPO) algorithm, in which a novel global multi-function cost is designed. The algorithm utilizes the advantage decomposition for policy updates in the way of credit assignment, resulting in more stable and efficient updates compared to traditional value decomposition. Moreover, to further enhance the performance of both observers and controllers, a sequential game is established between them, where observers’ policies are influenced by controllers’ optimal control and vice versa. Finally, the simulation results verify the effectiveness of the designed OHAPPO algorithm in the pursuit-evasion game. © 2004-2012 IEEE.

关键词： Reinforcement learning

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Finite-time stability and stabilization for highly nonlinear stochastic Markov jump systems

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ISA Transactions 2025年 160卷 131-138页

作者： Zhong, Shiyu Zhang, Weihai The College of Intelligent Manufacturing and Control Engineering Shandong Institute of Petroleum and Chemical Technology Dongying257061 China The College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

The research on finite-time stability (FTS) mainly focuses on linear and nonlinear systems, however, there are few studies on such problems for highly nonlinear systems. At present, most studies on FTS use the Lyapunov function method, and most of the results not only require the Lyapunov function in different modes to have the same feature, but also require the diffusion operators in different modes to be constrained by the same type of functions. This is somewhat restrictive to the selection of the Lyapunov function. Based on this, this paper concerns with FTS and asynchronous control of highly nonlinear stochastic Markov jump systems (HNSMJSs). Firstly, the criteria of mth moment finite-time stability (m-MFTS) for HNSMJSs in Lyapunov function form and parameter form are given and the asynchronous controller is provided to guarantee the mth moment finite-time stabilization (m-MFT stabilization). Moreover, HNSMJSs with deterministic time delay are extended to that with time-varying delay, and a more general result is given. Finally, three examples are provided to clarify the effectiveness of the proposed work. © 2025 International Society of automation

关键词： Lyapunov functions

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Adaptive control of a Flexible Manipulator With Unknown Hysteresis and Intermittent Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 148-158页

作者： Shouyan Chen Weitian He Zhijia Zhao Yun Feng Zhijie Liu Keum-Shik Hong School of Mechanical and Electrical Engineering Guangzhou University the School of Control Science and Engineering Shandong University IEEE the College of Electrical and Information Engineering Hunan University the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University the School of Intelligence Science and Technology University of Science and Technology Beijing (USTB) the Institute for Future the School of AutomationQingdao University the School of Mechanical Engineering Pusan National University

In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.

关键词： Adaptive control flexible manipulator intermittent actuator faults inverse hysteresis dynamics vibration control

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Adaptive Path-following control of Underactuated Surface Vessels Subject to Unknown Disturbances With Uniform Bounded Lateral Motion

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International Journal of control, automation and Systems 2025年 1-11页

作者： Cao, Duc Sang Tran, Quoc Van Department of Electric Actuators & Automation Control Control Automation in Production and Improvement of Technology Institute (CAPITI) Hanoi Viet Nam Department of Mechatronics the School of Mechanical Engineering Hanoi University of Science and Technology (HUST) Hanoi Viet Nam

This article presents a unified framework for path-following and trajectory tracking of underactuated surface vessels (USVs) in the presence of unknown disturbances. To handle the underactuation of the vessel, the path-following of a hand point in the longitudinal axis ahead of the vessel’s mass center is considered. Two robust adaptive path-following control laws are subsequently proposed in the vessel-fixed coordinates to drive the vessel (specifically, the hand point) to the desired path asymptotically. The first controller employs a time-varying discontinuous signum term to attenuate unknown disturbances. By utilization of normalization technique, the second tracking controller is continuous, thus eliminating chattering effect in the control forces commonly occurred in sliding mode controllers. Global uniform asymptotic stability of the path tracking is established based on Lyapunov theory and Barbalat’s lemma. As another technical contribution of this article, the stability of the non-actuated lateral motion of the vessel is shown rigorously based on the square-integrability of the path-following error vector. © ICROS, KIEE and Springer 2025.

关键词： Internal dynamics path-following robust adaptive control stability analysis underactuated vehicles

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Rolling Bearing Fault Diagnosis Based on MTF Encoding and CBAM-LCNN Mechanism

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Computers, Materials & Continua 2025年第3期82卷 4863-4880页

作者： Wei Liu Sen Liu Yinchao He Jiaojiao Wang Yu Gu School of Mechanical and Electrical Engineering Zhoukou Normal UniversityZhoukou466001China School of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132022China School of Automation Guangdong University of Petrochemical TechnologyMaoming525000China

To address the issues of slow diagnostic speed,low accuracy,and poor generalization performance in traditional rolling bearing fault diagnosis methods,we propose a rolling bearing fault diagnosis method based on Markov Transition Field(MTF)image encoding combined with a lightweight convolutional neural network that integrates a Convolutional Block Attention Module(CBAM-LCNN).Specifically,we first use the Markov Transition Field to convert the original one-dimensional vibration signals of rolling bearings into two-dimensional ***,we construct a lightweight convolutional neural network incorporating the convolutional attention module(CBAM-LCNN).Finally,the two-dimensional images obtained from MTF mapping are fed into the CBAM-LCNN network for image feature extraction and fault *** validate the effectiveness of the proposed method on the bearing fault datasets from Guangdong University of Petrochemical Technology’s multi-stage centrifugal fan and Case Western Reserve *** results show that,compared to other advanced baseline methods,the proposed rolling bearing fault diagnosis method offers faster diagnostic speed and higher diagnostic *** addition,we conducted experiments on the Xi’an Jiaotong University rolling bearing dataset,achieving excellent results in bearing fault *** results validate the strong generalization performance of the proposed *** method presented in this paper not only effectively diagnoses faults in rolling bearings but also serves as a reference for fault diagnosis in other equipment.

关键词： Rolling bearing fault diagnosis markov transition field lightweight convolutional neural network convolutional block attention module

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