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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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Chaos in pulsar spin dynamics

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IFAC-PapersOnLine 2023年第1期56卷 199-203页

作者： Berc Deruni Mustafa Dogan Department of Engineering Yeditepe University Istanbul 34755 Turkey Department of Control and Automation Engineering Faculty of Electrical-Electronics Engineering Istanbul Technical University Istanbul 34469 Turkey

In the present paper, a new model describing neutron star dynamics is analysed. The system under consideration can be described as a modified vortex creep model. Two component model and the vortex creep model have been used successfully to describe post glitch relaxation phase. However, glitch behaviour is yet to be explained. There can be a possible stochastic mechanism that trigger glitches in neutron stars. To this aim, we propose a modification in the nonlinear vortex creep model. The significance of the modification is twofold, the dynamics of the system is able to generate intermittency, imitating the glitch behaviour of pulsars, and the system also show chaotic motion when the system parameters are set accordingly. The chaotic dynamics is verified by using nonlinear tools such as numerical phase portraits, Lyapunov exponents and bifurcation diagrams.

关键词： Pulsar spin dynamics nonlinear superfluidity chaos intermittency

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Robust control of Feeding Speed for Coal Mine Tunnel Drilling Machines 25

Robust Control of Feeding Speed for Coal Mine Tunnel Drillin...

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25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Liu, Xiao Chen, Luefeng Wu, Min Cao, Weihua Lu, Chengda Pedrycz, Witold School of Automation China University of Geosciences Wuhan China School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Istinye University Department of Computer Engineering Sariyer Istanbul34396 Turkey

Changes in coal seam hardness cause fluctuations in the feed resistance at the drill bit during the drilling process, leading to unstable feeding speed. This paper proposes a robust dynamic output feedback controller to suppress disturbances caused by the variations in coal seam hardness in the feed system. Firstly, an unknown parameter measuring coal seam hardness is introduced, and an uncertain model of the feeding system is established based on the finite element model of the drill string. By designing weighted functions based on industrial field requirements and constructing a generalized plant, the controller achieves loop shaping, reducing the low-frequency impact of coal seam hardness variations on the feed system and suppressing the systems resonance peak. Simulation results demonstrate that the controller effectively suppresses parameter variations and external disturbances caused by changes in coal seam hardness, achieving stable control of the drilling speed. © 2024 IEEE.

关键词： Robust control

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Hybrid Oscillation Damping and Inertia Management for Distributed Energy Resources

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IEEE Transactions on Power Systems 2025年

作者： Feng, Cheng Huang, Linbin He, Xiuqiang Wang, Yi Dorfler, Florian Kang, Chongqing Tsinghua University Department of Electrical Engineering Beijing100084 China Zhejiang University College of Electrical Engineering Hangzhou310027 China Tsinghua University Department of Automation Beijing100084 China The University of Hong Kong Department of Electrical and Electronic Engineering Hong Kong Automatic Control Laboratory ETH Zurich8092 Switzerland

Power systems dominated by converter-interfaced distributed energy resources (DERs) typically exhibit weaker damping capabilities and lower inertia, compromising system stability. Although individual DER controllers are evolving to provide superior oscillation damping capabilities and inertia supports, there is a lack of network-wide coordinated management measures for multiple DERs, potentially leading to unexpected instability and cost-effectiveness problems. To address this gap, this paper introduces a hybrid oscillation damping and inertia management strategy for multiple DERs, considering network coupling effects, and seeks to encourage DERs to provide enhanced damping and inertia with appropriate economic incentives. We first formulate an optimization problem to tune and allocate damping and inertia coefficients for DERs, minimizing associated power and energy costs while ensuring hard constraints for system frequency stability and small-signal stability. The problem is built upon a novel convex parametric formulation that integrates oscillation mode location and frequency trajectory requirements, equipped with a theoretical guarantee, and eliminating the need for iterative tuning and computation burdens. Furthermore, to increase the willingness of DERs to cooperate, we further design appropriate economic incentives to compensate for DERs' costs based on the proposed cost minimization problem, and assess its impact on system cost-efficiency. Numerical tests highlight the effectiveness of the proposed method in promoting system stability and offer insights into potential economic benefits. © 1969-2012 IEEE.

关键词： Damping

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Robust IMC for Time Delay Attack Compensation of Renewable Supported Power System

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IEEE Transactions on automation Science and engineering 2025年 22卷 16532-16546页

作者： Pawan Kumar Pathak Anil Kumar Yadav Innocent Kamwa School of Automation Banasthali Vidyapith Jaipur Rajasthan India Department of Instrumentation and Control Engineering Dr B R Ambedkar National Institute of Technology Jalandhar Jalandhar Punjab India Department of Electrical Engineering College of Engineering Université Laval Quebec QC Canada

This study presents the design of a robust control strategy utilizing an internal model control (IMC)-based proportional integral-one plus derivative with filter (PI-(1+DF)) controller to mitigate the impact of time-delay attacks (TDAs) on renewable-integrated power system (PS). Before implementing mitigation, an adaptive recursive least square filter with a forgetting factor (ARLS-FF) is employed as an online detection mechanism for TDAs. The design methodology incorporates Kharitonov’s stability theorem to identify the worst-case plant, for which the proposed controller parameters are obtained using the IMC framework. A critical feature of IMC structure is the filter coefficient $({\mu })$ , which is determined based on the maximum inverse sensitivity ${(\boldsymbol {M}_{\boldsymbol {T}}}\boldsymbol {)}$ and the characteristics of considered TDA, underscoring the proposed control scheme’s enhanced efficacy. Stability under time-varying attacks is rigorously analyzed through the Lyapunov-Krasovskii function (LKF) and linear matrix inequalities (LMIs) based approach with vivid robustness assessment ensuring resilience to parametric uncertainties. Finally, benchmarking on the IEEE-39 and IEEE-118 bus systems validates the proposed controller’s superiority on large-scale and realistic interconnected PSs. Note to Practitioners—In PS operations, TDAs are among the most serious cyber threats, with the potential to destabilize the system and even cause blackouts in extreme cases. As a result, TDAs have become a growing focus in PS research. This study introduces IMC-based robust load frequency control (LFC) designed to counteract TDAs, thereby improving the effectiveness of current LFC techniques. The controller is designed for a TDA of 2s but demonstrates robust performance up to 4s of TDA. The proposed IMC-PI-(1+DF) control architecture’s effectiveness is evaluated under various practical scenarios, including constant TDAs, stochastic time-delayed cyber-attacks (STCAs),

关键词： Stability criteria Delays Power system stability Indexes Prevention and mitigation Vectors Uncertainty Electronic mail Detectors Delay effects

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Time-Attention Graph Convolutional Network Soft Sensor in Biochemical processes 4

Time-Attention Graph Convolutional Network Soft Sensor in Bi...

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Jia, Mingwei Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Most data-driven soft sensor methods can model nonlinear time-varying characteristics of biochemical processes. However, the intrinsic relationship between variables, which is helpful for understanding model behavior, has rarely been investigated in existing data-driven methods. In this work, a novel soft sensor model of time-attention graph convolutional network (TA-GCN) is proposed, which jointly leverages variable relationships and long-term temporal dependencies to improve interpretability and prediction accuracy. This model first uses the maximum information coefficient to construct a topology graph and trains edge strengths end-to-end. The data are then encoded in the spatial-temporal dimension based on GCN and attention mechanism. Finally, the empirical knowledge that analyzes the operating state of the process and graph are combined to explain the model behavior. In comparison to existing soft sensors, TA-GCN enables efficient and scalable training for long-term spatial-temporal dependencies. Experimental results on InPenSim dataset demonstrate that TA-GCN is competitive with state-of-the-art methods. © 2022 IEEE.

关键词： Convolution

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A Cloud-Edge-Based Multi-Label Learning and Fast Clustering Method for Emerging New PV Faults 13

A Cloud-Edge-Based Multi-Label Learning and Fast Clustering ...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent Systems, CYBER 2023

作者： Liu, Qi Yang, Bo Liu, Yuxiang Ma, Kai Guan, Xinping Shanghai Jiao Tong University Ministry of Education Key Laboratory of System Control and Information Processing Department of Automation Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

ISBN: (纸本)9798350315196

Aiming at accurate identification of emerging new faults in PV systems, a novel PV fault diagnosis framework based on cloud-edge collaboration is designed. Model updates are deployed on the cloud servers, while real-time diagnosis is implemented at the edge devices. A multi-label learning model is developed to extract fault features efficiently, and a threshold scheme is further designed for feature enhancement. The obtained features are processed by K-Means clustering and the One-Class Support Vector Machine (OCSVM) methods, which can accurately diagnose existing types and identify unknown faults. For analysis and demonstration, the Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor Embedding (t-SNE) methods are used for dimensionality reduction and visualization. Numerical results validate the effectiveness of the proposed method. © 2023 IEEE.

关键词： K-means clustering

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Fault localization for intelligent automation systems 28

Fault localization for intelligent automation systems

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28th IEEE International Conference on Emerging Technologies and Factory automation, ETFA 2023

作者： Eros, Endre Bengtsson, Kristofer Åkesson, Knut Chalmers University of Technology Automation Research Group Electrical Engineering Systems and Control Department Gothenburg Sweden Volvo Group As Senior Researcher for Smart and Connected Operations Research and Technology Development Gothenburg Sweden

ISBN: (纸本)9798350339918

Conventional programming of explicit control code is unsuitable for flexible and collaborative production systems. A model-based approach, which focuses on defining capabilities of a system, instead of specifying how to achieve them, provides an alternative for creating complex, scalable, and reliable systems. This is accomplished through the use of behavior models, and tools such as planning, synthesis, verification, and testing. However, developing such models is not without challenges, as it is possible to overlook or incorrectly specify potential behavior and constraints. This can result in unsolvable planning problems or plans that are invalid for other reasons. When plans are unobtainable, developers receive no feedback, which makes model adjustments a difficult and time-intensive task. This paper recognizes these challenges as crucial barriers for adopting model-based development of intelligent automation systems. To facilitate the development of such systems, an approach for detecting and localizing faults in behavior models is presented. Drawing inspiration from software fault localization techniques, the proposed method involves identifying suspicious resources, variables, and operations. The effectiveness of this approach is illustrated with an example use case. © 2023 IEEE.

关键词： automation

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Topology-Informed Graph Convolutional Network for Fault Diagnosis 11

Topology-Informed Graph Convolutional Network for Fault Diag...

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11th IEEE Data Driven control and Learning Systems Conference, DDCLS 2022

作者： Jia, Mingwei Liu, Yi Xu, Danya Yang, Tao Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering 30013 Taiwan

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

The development of an accurate data-driven fault diagnosis model faces several obstacles. One significant challenge is how to combine the model with the process mechanism rationally and improve the model interpretability. In this work, a fault diagnosis method based on a topology-informed graph convolutional network (TIGCN) is proposed. This model first uses the empirical knowledge that analyzes the operating state of the process and combines the operating data to construct a signed directed graph. Then the operating data is divided into three modalities in the time dimension. The model utilizes a well-designed spatial-temporal convolutional layer and signed directed graph to construct different modalities separately to effectively detect fault types. The superior fault diagnosis performance of the proposed TIGCN model is demonstrated on the Tennessee-Eastman process as compared to traditional approaches. © 2022 IEEE.

关键词： Failure analysis

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Acoustic wireless communication based on parameter modulation and complex Lorenz chaotic systems with complex parameters and parametric attractors

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Chinese Physics B 2021年第8期30卷 248-259页

作者： Fang-Fang Zhang Rui Gao Jian Liu Department of Control Science and Engineering Shandong UniversityJinan 250061China Department of Electrical Engineering and Automation Qilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Mathematical Sciences University of JinanJinan 250022China

As the competition for marine resources is increasingly fierce,the security of underwater acoustic communication has attracted a great deal of *** information and location of the communicating platform can be leaked during the traditional underwater acoustic communication *** to the unique advantages of chaos communication,we put forward a novel communication scheme using complex parameter modulation and the complex Lorenz ***,we design a feedback controller and parameter update laws in a complex-variable form with rigorous mathematical proofs(while many previous references on the real-variable form were only special cases in which the imaginary part was zero),which can be realized in practical engineering;then we design a new communication scheme employing parameter *** main parameter spaces of the complex Lorenz system are discussed,then they are adopted in our communication *** also find that there exist parametric attractors in the complex Lorenz *** make numerical simulations in two channels for digital signals and the simulations verify our conclusions.

关键词： parameter modulation identification chaotic system acoustic wireless communication

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