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Adaptive fuzzy security control of uncertain semi-Markov jump cyber-physical systems with stochastic perturbation

Cyber-Physical Systems 2025年

作者： Xun, Tengteng Liu, Zhen Jiang, Baoping School of Automation Shandong Key Laboratory of Industrial Control Technology Qingdao University Qingdao China School of Electronic and Information Engineering Suzhou University of Science and Technology Suzhou China

A novel adaptive secure control strategy is proposed for uncertain stochastic semi-Markov jump cyber-physical systems utilizing fuzzy sliding mode control (FSMC) technology, where the studied plants are affected by actuator attacks (AAs), actuator failures (AFs), stochastic perturbations and unknown transition rates. This strategy not only constrains the state trajectory to the constructed sliding mode surface (SMS) during limited period, but also ensures that the uncertain system operates with control requirements against unknown AAs and AFs, and the stochastic stability condition is derived by integrating SMS reachability with stochastic control theory. Finally, simulation results exhibit the feasibility of the proposed algorithm. © 2025 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Markov processes

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Non-singular Fast Terminal Sliding Mode and Active Disturbance Rejection control for Quadrotor UAV

Non-singular Fast Terminal Sliding Mode and Active Disturban...

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IEEE International Conference on Unmanned Systems (ICUS)

作者： Cheng Chen Yunping Liu Tingting Zhang Yuanxin Sun Jingwei Shi School of Automation Nanjing University of Information Science and Technology Nanjing China School of Command and Control Engineering Army Engineering University of PLA Nanjing China

ISBN: (数字)9798350384185

ISBN: (纸本)9798350384192

The purpose of this paper is to improve the anti-interference ability of the quadrotor UAV. This paper proposes a non-singular fast terminal sliding mode combined with an active disturbance rejection controller. Firstly, the uncertainty factors, such as model errors and internal and external disturbances of the quadrotor UAV system, are regarded as lumped disturbances, estimated and compensated online by the extended state observer in real-time. According to its underactuated, multivariable, and nonlinear characteristics, it is divided into a position loop and an attitude loop. On this basis, it is transformed into complete drive control by introducing virtual control quantity. The simulation results show that the non-singular fast terminal sliding mode active disturbance rejection controller has better robustness than the cascade active disturbance rejection control.

关键词： Robust control Uncertainty Autonomous systems Simulation Prototypes Autonomous aerial vehicles Robustness Real-time systems State estimation Quadrotors

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Adaptive gain-scheduling control for uncertain Markovian jump systems. A transition rate synthesis method 37

Adaptive gain-scheduling control for uncertain Markovian jum...

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Cao, Zhiru Zhu, Kaiqun Zhang, Zhina East China University of Science and Technology School of Information Science and Engineering China Shanghai University School of Mechatronic Engineering and Automation Shanghai China University of Shanghai for Science and Technology Department of Control Science and Engineering Shanghai China Anhui Polytechnic University School of Mathematics-Physics and Finance Wuhu China

ISBN: (纸本)9781665465366

This paper is concerned with the gain-scheduling control for a class of uncertain Markovian jump systems, in which the uncertainties are described via the polytopic representation. In order to reduce the conservatism brought from the common/parameter-independent control method in existing results, an adaptive gain-scheduling controller is designed whose gain is constructed as a convex sum of a fixed set of controller gains. Under the assumption of a given transition rate matrix, the controller gains and adaption laws of polytopic parameters are co-designed to ensure the stochastic stability of the resultant closed-loop system. Furthermore, taking the characteristic of Markovian transition rates, a co-designed scheme is developed to obtain controller gains, transition rate matrix, and adaption laws, simultaneously. Finally, a numerical example is adopted to illustrate the proposed method. © 2022 IEEE.

关键词： Closed loop systems

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STGSA:A Novel Spatial-Temporal Graph Synchronous Aggregation Model for Traffic Prediction

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 226-238页

作者： Zebing Wei Hongxia Zhao Zhishuai Li Xiaojie Bu Yuanyuan Chen Xiqiao Zhang Yisheng Lv Fei-Yue Wang the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the Shandong Key Laboratory of Smart Transportation(Preparation) Shandong Jiao Tong UniversityShanghai 200240China the College of Science China University of PetroleumQingdao 266580China the Department of Transportation Engineering School of Transportation Science and TechnologyHarbin Institute of TechnologyHarbin 150090China IEEE

The success of intelligent transportation systems relies heavily on accurate traffic prediction,in which how to model the underlying spatial-temporal information from traffic data has come under the *** existing frameworks typically utilize separate modules for spatial and temporal correlations ***,this stepwise pattern may limit the effectiveness and efficiency in spatial-temporal feature extraction and cause the overlook of important information in some ***,it is lacking sufficient guidance from prior information while modeling based on a given spatial adjacency graph(e.g.,deriving from the geodesic distance or approximate connectivity),and may not reflect the actual interaction between *** overcome those limitations,our paper proposes a spatial-temporal graph synchronous aggregation(STGSA)model to extract the localized and long-term spatial-temporal dependencies ***,a tailored graph aggregation method in the vertex domain is designed to extract spatial and temporal features in one graph convolution *** each STGSA block,we devise a directed temporal correlation graph to represent the localized and long-term dependencies between nodes,and the potential temporal dependence is further fine-tuned by an adaptive weighting ***,we construct an elaborated spatial adjacency matrix to represent the road sensor graph by considering both physical distance and node similarity in a datadriven ***,inspired by the multi-head attention mechanism which can jointly emphasize information from different r epresentation subspaces,we construct a multi-stream module based on the STGSA blocks to capture global *** projects the embedding input repeatedly with multiple different ***,the predicted values are generated by stacking several multi-stream *** experiments are constructed on six real-world datasets,and numerical results show that the proposed STGSA

关键词： Deep learning graph neural network(GNN) multistream spatial-temporal feature extraction temporal graph traffic prediction

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Switching GMM-HMM for Complex Human Activity Modeling and Recognition

Switching GMM-HMM for Complex Human Activity Modeling and Re...

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2022 Chinese automation Congress, CAC 2022

作者： Qin, Weiwei Wu, Huai-Ning Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Peng Cheng Laboratory Shenzhen518000 China

ISBN: (纸本)9781665465335

Complex human activities can be decomposed into primitive activities (PAs) that happen sequentially but may vary in order or frequency among different observation sequences. The Gaussian mixture model based hidden Markov model (GMM-HMM) is widely used for activity modeling but is only capable of modeling activities with fixed pattern trajectories. To overcome the drawback of GMM-HMM, a hierarchical structure is introduced to form the Switching Gaussian mixture model based hidden Markov model (S-GMMHMM), where PAs are treated as upper layer states and the continuous observation sequence emitted by each PA is modeled by a GMM-HMM. To ensure that the upper layer states correspond to real activities, a supervised algorithm is proposed for S-GMMHMM parameter estimation. For the purpose of less time complexity, a real-time activity recognition algorithm is proposed by computing activity posteriors recursively. Experiment results show that the proposed model outperforms GMM-HMM in activity recognition, while brings a notable reduction in time complexity. © 2022 IEEE.

关键词： Hidden Markov models

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Fault-Tolerant control for Launch Vehicle Actuator Based on Adaptive control

Fault-Tolerant Control for Launch Vehicle Actuator Based on ...

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International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Niu, Qiushi Li, Qingdong Liu, Yishi Han, Liang Ren, Zhang School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China School of Sino-French Engineer Beihang University Beijing100191 China

ISBN: (纸本)9789811581540

A fault-tolerant control for launch vehicle actuator with actuator faults is proposed assuming the fault has been diagnosed in this paper. Firstly, the model for the launch vehicle with actuator failures is established considering faults. The tracking differentiator is used to process the angle signal of the program for the subsequent controller design. Using the attitude angle and angular velocity information measured by the control components, a basic controller is designed by LQR method to make the launch vehicle stable, thus a reference model with good stability is obtained. Moreover, the adaptive control law is designed in the form of integral by means of model reference adaptive control (MRAC) method to ensure attitude stability in flight. Finally, the validity of the algorithm was verified by simulation. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Model reference adaptive control

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Multi-agent Deep Reinforcement Learning Based Multi-objective Charging control for Electric Vehicle Charging Station 7th

Multi-agent Deep Reinforcement Learning Based Multi-objectiv...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Gong, Jiabao Fu, Weiming Kang, Yu Qin, Jiahu Xiao, Feng Department of Automation University of Science and Technology of China Hefei230027 China State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819733279

This paper proposes a multi-agent deep reinforcement learning (MADRL) based algorithm for charging control of multiple electric vehicles (EVs) in an electric vehicle charging station (EVCS) with dynamic operations. By taking the uncertainties of EV users’ behaviors and charging prices into consideration, a Markov game with multiple objectives is first established, where the individual objective of reducing EV charging costs and the collective objective of mitigating charging load fluctuations are both studied. Then, a multi-agent actor-double-critic (MAADC) algorithm with a unified advantage actor-critic framework is proposed, where two advantage functions are designed as the local and global critics, and the integrated actor is employed to balance the learning towards the individual and collective objectives. The simulation results obtained in a delicately built EVCS environment show the effectiveness of MAADC. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Reinforcement learning

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Distributed Optimization with Finite Bit Adaptive Quantization for Efficient Communication and Precision Enhancement 63

Distributed Optimization with Finite Bit Adaptive Quantizati...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Artificial Intelligence Thrust of the Information Hub Guangzhou China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Clear Water Bay Hong Kong Aalto University School of Electrical Engineering Department of Electrical Engineering and Automation Espoo Finland University of Cyprus School of Engineering Department of Electrical and Computer Engineering Nicosia1678 Cyprus Kth Royal Institute of Technology Division of Decision and Control Systems StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

In realistic distributed optimization scenarios, individual nodes possess only partial information and communicate over bandwidth constrained channels. For this reason, the development of efficient distributed algorithms is essential. In our paper we addresses the challenge of unconstrained distributed optimization. In our scenario each node's local function exhibits strong convexity with Lipschitz continuous gradients. The exchange of information between nodes occurs through 3-bit bandwidth-limited channels (i.e., nodes exchange messages represented by a only 3 -bits). Our proposed algorithm respects the network's bandwidth constraints by leveraging zoom-in and zoom-out operations to adjust quantizer parameters dynamically. We show that during our algorithm's operation nodes are able to converge to the exact optimal solution. Furthermore, we show that our algorithm achieves a linear convergence rate to the optimal solution. We conclude the paper with simulations that highlight our algorithm's unique characteristics. © 2024 IEEE.

关键词： Bandwidth

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A Novel Cross-Ratio Based Gaze Estimation Method

A Novel Cross-Ratio Based Gaze Estimation Method

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2022 International Conference on Machine Learning and Knowledge engineering, MLKE 2022

作者： Fan, Shuo Chi, Jiannan Liu, Jiahui University of Science and Technology Beijing School of Automation and Electrical Engineering Beijing China Engineering Research Center of Intelligence Perception and Autonomous Control Ministry of Education Beijing China

ISBN: (纸本)9781665495677

Eye movement is the most natural expression of human thoughts, therefore it plays an important role in human-computer interaction. Over the past few decades, researchers have been pursuing for high-accuracy, easy-to-use eye-tracking techniques. The gaze tracking technology based on cross-ratio is a hot topic in the field due to its advantages of simple hardware device and allowing free head movement. Given the complexity of the user calibration procedure and the error caused by the coplanar assumption in the cross-ratio based method, we propose a new method to approximate the pupil plane step by step through constructing the front and rear planes, and then estimate the point-of-regard based on cross-ratio invariance. Simulation results show that the proposed method not only simplifies the system configuration and user calibration procedure, but also avoids the error caused by the non-coplanarity between the corneal surface reflection points and the pupil center. © 2022 IEEE.

关键词： Eye tracking

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Cascaded Extended State Observer-Based Sliding Mode control for DC-DC Converter with Time- Varying Power Fluctuation

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IEEE Transactions on Industry Applications 2022年 1-6页

作者： Xu, Liangcai Liu, Jianxing Zhuo, Shengrong Huangfu, Yigeng Gao, Fei School of Automation Northwestern Polytechnical University Xi'an China Department of Control Science and Engineering Harbin Institute of Technology Harbin China FEMTO-ST Institute Univ. Bourgogne Franche-Comte UTBM CNRS Belfort France

In this paper, a cascaded extended state observer- based sliding mode control (SMC) is proposed for the typical microgrid (MG) interfaced dc-dc boost converter. For a given MG system, the power fluctuation is unpredictable, which may cause an unstable dc-bus voltage. In that situation, all the dc-bus connected electronic loads cannot work normally. In order to maintain a stable dc-bus voltage, additional power sources with a suitable power converter and the advanced controller are necessary. Especially, the controller for the power converter plays a crucial role in reducing the power fluctuation and regulating the dc-bus voltage. In this paper, to improve the ability of the converters to reject external power disturbance, a cascaded extended state observer is designed to estimate the lumped disturbance more accurately. Besides, the continuous SMC method is adopted to provide a feedback control loop. The corresponding simulation results could highly validate the effectiveness of the proposed control method. IEEE

关键词： Sliding mode control

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