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Input Structure Design for Structural controllability of Complex Networks

IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1571-1581页

作者： Lifu Wang Zhaofei Li Guotao Zhao Ge Guo Zhi Kong School of Control Engineering Northeastern University at QinhuangdaoQinhuangdao 066004China School of Control Engineering Northeastern University at QinhuangdaoQinhuangdao 066004 School of Automation Beijing Institute of TechnologyBeijing 100081China

This paper addresses the problem of the input design of large-scale complex *** types of network components,redundant inaccessible strongly connected component(RISCC)and intermittent inaccessible strongly connected component(IISCC)are defined,and a subnetwork called a driver network is *** on these,an efficient method is proposed to find the minimum number of controlled nodes to achieve structural complete controllability of a network,in the case that each input can act on multiple state *** range of the number of input nodes to achieve minimal control,and the configuration method(the connection between the input nodes and the controlled nodes)are *** possible input solutions can be obtained by this ***,we give an example and some experiments on real-world networks to illustrate the effectiveness of the method.

关键词： Complex network input configuration minimum controlled node set structural controllability

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Distributed Secure Surrounding control for Multiple USVs against Deception Attacks: A Stackelberg Game Approach with Reinforcement Learning

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-12页

作者： Wang, Qiang Liu, Chun Lan, Jianglin Ren, Xiaoqiang Meng, Yizhen Wang, Xiaofan School of Mechatronic Engineering and Automation Shanghai University Shanghai China School of Mechatronic Engineering and Automation James Watt School of Engineering University of Glasgow Glasgow U.K Shanghai Aerospace Control Technology Institute

This article investigates the Stackelberg game-based distributed secure surrounding control (SSC) problem for multiple unmanned surface vehicles (USVs) with unknown dynamics under deception attacks (DAs). The proposed scheme is rooted in the Stackelberg game with reinforcement learning (RL), in which the attacker and controller respectively play the roles of the follower and leader, making sequential decisions of the DA and the SSC. Specifically, a distributed target estimator is established to access the target position. By utilizing this estimated position to formulate an intermediate control law, the target surrounding scenario is effectively transformed into the Stackelberg game-solving problem. The RL approach with a neural networks-based actor-critic learning structure is deployed to directly derive the distributed optimal SSC and DA policies from the Bellman error, whilst learning the unknown dynamics of USVs. Moreover, a value function decomposition technique is applied optimally for using the designed control parameters, thereby accelerating the acquisition of optimal policies. A rigorous theoretical analysis is employed to ensure the closed-loop stability of multiple USVs. Simulations are provided to validate the effectiveness of the proposed distributed SSC scheme for multiple USVs. IEEE

关键词： Reinforcement learning

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Computational and experimental investigations of a microfluidic mixer for efficient iodine extraction using carbon tetrachloride enhanced with gas bubbles

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Chinese Physics B 2023年第11期32卷 518-526页

作者： Siddique Muhammad Kashif 孙林李松晶 Department of Fluid Control and Automation School of Mechatronics EngineeringHarbin Institute of TechnologyHarbin 150001China

Numerous studies have been conducted on microfluidic mixers in various microanalysis systems, which elucidated the manipulation and control of small fluid volumes within microfluidic chips. These studies have demonstrated the ability to control fluids and samples precisely at the microscale. Microfluidic mixers provide high sensitivity for biochemical analysis due to their small volumes and high surface-to-volume ratios. A promising approach in drug delivery is the rapid microfluidic mixer-based extraction of elemental iodine at the micro level, demonstrating the versatility and the potential to enhance diagnostic imaging and accuracy in targeted drug delivery. Micro-mixing inside microfluidic chips plays a key role in biochemical analysis. The experimental study describes a microfluidic mixer for extraction of elemental iodine using carbon tetrachloride with a gas bubble mixing process. Gas bubbles are generated inside the microcavity to create turbulence and micro-vortices resulting in uniform mixing of samples. The bubble mixing of biochemical samples is analyzed at various pressure levels to validate the simulated results in computational fluid dynamics(CFD). The experimental setup includes a high-resolution camera and an air pump to observe the mixing process and volume at different pressure levels with time. The bubble formation is controlled by adjusting the inert gas flow inside the microfluidic chip. Microfluidic chip-based gas bubble mixing effects have been elaborated at various supplied pressures.

关键词： microfluidic mixer iodine extraction CFD simulation micro-mixing properties

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Multi-step state-based opacity for unambiguous weighted machines

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Science China(Information Sciences) 2024年第11期67卷 211-221页

作者： Zhipeng ZHANG Chengyi XIA Guoyuan QI Jun FU School of Artificial Intelligence Tiangong University School of Control Science and Engineering Tiangong University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University

Opacity is a central concept in the issue of privacy security and has been studied extensively in fields such as finite automata, probabilistic automata, and stochastic automata. Here, we investigate the problem of validating multi-step opaque properties through unambiguous weighted machines from the perspective of cyber-physical systems. First, the notion of multi-step state-based opacity for unambiguous weighted machines is presented and defined. It includes two variants of delays with a finite K and infinite steps. Subsequently, the weighted state estimate with K(infinite)-step delay is established by abstracting the possible state set that the system could have through these weighted observations. Meanwhile, to keep the observable weighted sequence consistent between the bidirectional observers, the unobserved weights of the reverse weighted machine are assumed to be reserved. Subsequently, the existence conditions are developed, and the corresponding algorithms, termed the weighted bidirectional observer, are generalized to verify these properties. Finally, several numerical examples are illustrated to demonstrate the effectiveness of the proposed method. Taken together, the current approach will be conducive to a deep understanding of the security and privacy of cyber-physical systems.

关键词： logical dynamical systems weighted state machine state estimation opacity cyber physical systems

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Linear Quadratic Optimal control for Systems Governed by First-Order Hyperbolic Partial Differential Equations

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Journal of Systems Science & Complexity 2024年第1期37卷 230-252页

作者： XUE Xiaomin XU Juanjuan ZHANG Huanshui School of Control Science and Engineering Shandong UniversityJinan 250061China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266000China

This paper focuses on linear-quadratic(LQ)optimal control for a class of systems governed by first-order hyperbolic partial differential equations(PDEs).Different from most of the previous works,an approach of discretization-then-continuousization is proposed in this paper to cope with the infinite-dimensional nature of PDE *** contributions of this paper consist of the following aspects:(1)The differential Riccati equations and the solvability condition of the LQ optimal control problems are obtained via the discretization-then-continuousization method.(2)A numerical calculation way of the differential Riccati equations and a practical design way of the optimal controller are ***,the relationship between the optimal costate and the optimal state is established by solving a set of forward and backward partial difference equations(FBPDEs).(3)The correctness of the method used in this paper is verified by a complementary continuous method and the comparative analysis with the existing operator results is *** is shown that the proposed results not only contain the classic results of the standard LQ control problem of systems governed by ordinary differential equations as a special case,but also support the existing operator results and give a more convenient form of computation.

关键词： Discretization-then-continuousization method first-order hyperbolic partial differential equations forward and backward partial difference equations linear quadratic optimal control.

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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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Multi-AAV Energy-Efficient Detection Coverage Under Jamming Environment: A Hierarchical Collaborative Learning Approach

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IEEE Transactions on Vehicular Technology 2025年第5期74卷 7351-7363页

作者： Fang, Chao Feng, Yanxiang Li, Xiaoling Yang, Yikang Xi'an Jiaotong University School of Automation Science and Engineering Xi'an710049 China Chang'an University School of Electronics and Control Engineering Xi'an710064 China

Autonomous aerial vehicles (AAVs) can provide detection coverage service in many scenarios. The fair coverage is achieved by designing carefully AAVs' trajectories, which are established at each step by choosing the moving action and channel access for transmitting data. However, under the jamming environment, the problematic trajectories could lead to mutual interference and malicious jamming, such that the coverage service fails. The selections of moving action and channel access are usually coupled, and so far no work has addressed them jointly for planning trajectory. As such, this paper investigates the multi-AAV joint optimization of moving action and channel access for the energy-efficient detection coverage. To decouple the strongly-coupled moving action and channel access, we model the studied optimization problem as a hierarchical game, where the stochastic game (resp. potential game) is applied for selecting moving action (resp. channel access). Then, we propose a multi-agent hierarchical cooperative learning (MAHCL) algorithm to attain near-optimal solution for the joint optimization. It is proved that the proposed MAHCL algorithm can asymptotically converge to the near-optimal joint strategy with lower computational complexity. Finally, the simulation results show the higher energy efficiency of MAHCL algorithm compared with the benchmarks. © 1967-2012 IEEE.

关键词： Stochastic systems

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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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Stability and Stabilization of Sampled-Data Based LFC for Power Systems:A Data-Driven Method

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 291-293页

作者： Yu-Long Fan Chuan-Ke Zhang Yong He the School of Automation China University of Geosciences the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education IEEE

Dear Editor,This letter is concerned with stability analysis and stabilization design for sampled-data based load frequency control(LFC) systems via a data-driven method. By describing the dynamic behavior of LFC systems based on a data-based representation, a stability criterion is derived to obtain the admissible maximum sampling interval(MSI) for a given controller and a design condition of the PI-type controller is further developed to meet the required MSI. Finally, the effectiveness of the proposed methods is verified by a case study.

关键词： Sampled data control systems

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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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