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Stress analysis and structural optimisation of insulating rods under dynamic and static loads

High Voltage 2025年第1期10卷 116-125页

作者： Haifeng Jin Lijun Jin Department of Control Science and Engineering Tongji UniversityShanghaiChina

This study aims to provide a theoretical basis for the fatigue characteristics and structural optimisation of insulating rods to enhance their reliability and lifespan in practical *** paper uses COMSOL to complete the stress analysis of insulating rods under dynamic and static loads based on the finite element *** correctness of the model is verified based on the elastic-plastic *** simulation results show that under the same load,the stress concentration area is more affected by the dynamic load,and the stress concentration position is highly consistent with the fracture position of the rod in the *** verifies the impact on the insulating rods at different speeds and static load *** shows that,in cases where the allowable stress is exceeded,as the number of operations increases,the fatigue characteristics will greatly affect the service life of the insulation ***,the fatigue analysis and structural optimisation of the insulating rod were completed,providing important reference values for the long-term stable operation of ultra-high voltage circuit breakers.

关键词： fatigue structural dynamic

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Privacy-preserving filtering, control and optimization for industrial cyber-physical systems

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science China(Information sciences) 2025年第4期68卷 267-283页

作者： Derui DING Qing-Long HAN Xiaohua GE Xian-Ming ZHANG Jun WANG Department of Control Science and Engineering University of Shanghai for Science and Technology School of Engineering Swinburne University of Technology Department of Computer Science City University of Hong Kong

Industrial cyber-physical systems closely integrate physical processes with cyberspace, enabling real-time exchange of various information about system dynamics, sensor outputs, and control decisions. The connection between cyberspace and physical processes results in the exposure of industrial production information to unprecedented security risks. It is imperative to develop suitable strategies to ensure cyber security while meeting basic performance *** the perspective of control engineering, this review presents the most up-to-date results for privacy-preserving filtering,control, and optimization in industrial cyber-physical systems. Fashionable privacy-preserving strategies and mainstream evaluation metrics are first presented in a systematic manner for performance evaluation and engineering *** discussion discloses the impact of typical filtering algorithms on filtering performance, specifically for privacy-preserving Kalman filtering. Then, the latest development of industrial control is systematically investigated from consensus control of multi-agent systems, platoon control of autonomous vehicles as well as hierarchical control of power systems. The focus thereafter is on the latest privacy-preserving optimization algorithms in the framework of consensus and their applications in distributed economic dispatch issues and energy management of networked power systems. In the end, several topics for potential future research are highlighted.

关键词： industrial cyber-physical systems privacy preservation distributed control distributed optimization power systems

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Application of feedforward and recurrent neural networks for model-based control systems

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control Theory and Technology 2025年第1期23卷 91-104页

作者： Marek Krok Wojciech P.Hunek Szymon Mielczarek Filip Buchwald Adam Kolender Department of Control Science and Engineering Opole University of TechnologyOpolePoland

In this paper,a new study concerning the usage of artificial neural networks in the control application is *** is shown,that the data gathered during proper operation of a given control plant can be used in the learning process to fully embrace the control ***,the instances driven by neural networks have the ability to outperform the original analytically driven *** different control schemes,namely perfect,linear-quadratic,and generalized predictive controllers were used in the theoretical *** addition,the nonlinear recurrent neural network-based generalized predictive controller with the radial basis function-originated predictor was obtained to exemplify the main results of the paper regarding the real-world application.

关键词： Predictive control Linear-quadratic control Inverse problems Feedforward network Recurrent neural network Optimization

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From Static and Dynamic Perspectives:A Survey on Historical Data Benchmarks of control Performance Monitoring

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 300-316页

作者： Pengyu Song Jie Wang Chunhui Zhao Biao Huang the State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University IEEE the Department of Chemical and Materials Engineering University of Alberta

In recent decades, control performance monitoring(CPM) has experienced remarkable progress in research and industrial applications. While CPM research has been investigated using various benchmarks, the historical data benchmark(HIS) has garnered the most attention due to its practicality and effectiveness. However, existing CPM reviews usually focus on the theoretical benchmark, and there is a lack of an in-depth review that thoroughly explores HIS-based methods. In this article, a comprehensive overview of HIS-based CPM is provided. First, we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo: static and dynamic properties. The static property portrays time-independent variability in system output, and the dynamic property describes temporal behavior driven by closed-loop feedback. Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two ***, two mainstream solutions for CPM methods are summarized, including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior. Furthermore, this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.

关键词： control performance monitoring (CPM) data-driven method historical data benchmark (HIS) industrial process performance index static and dynamic analysis

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Distributed coordination control of multi-agent systems under intermittent sampling and communication: a comprehensive survey

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science China(Information sciences) 2025年第5期68卷 289-331页

作者： Xiaohua GE Qing-Long HAN Xian-Ming ZHANG Derui DING Boda NING School of Engineering Swinburne University of Technology Department of Control Science and Engineering University of Shanghai for Science and Technology Department of Electrical and Electronic Engineering Auckland University of Technology

Sampling and communication are both crucial for coordination in multi-agent systems(MASs), with sampling capturing raw data from the environment for control decision making, and communication ensuring the data is shared effectively for synchronized and informed control decisions across agents. However, practical MASs often operate in environments where continuous and synchronous data samplings and exchanges are impractical, necessitating strategies that can handle intermittent sampling and communication constraints. This paper provides a comprehensive survey of recent advances in distributed coordination control of MASs under intermittent sampling and communication, focusing on both foundational principles and state-of-the-art techniques. After introducing fundamentals, such as communication topologies,agent dynamics, control laws, and typical coordination objectives, the distinctions between sampling and communication are elaborated, exploring deterministic versus random, synchronous versus asynchronous, and instantaneous versus sequential scenarios. A detailed review of emerging trends and techniques is then presented, covering time-triggered, event-triggered,communication-protocol-based, and denial-of-service-resilient coordination control. These techniques are analyzed across various attack models, including those based on data loss, sampled data, time constraints, and topology switching. By synthesizing these developments, this survey aims to equip researchers and practitioners with a clearer understanding of current challenges and methodologies, concluding with insights into promising future directions.

关键词： multi-agent systems distributed coordination control sampled-data control event-triggered control resilient control denial-of-service attacks communication protocols event-triggered mechanisms

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Adaptive torque estimation-based nonlinear H∞ control of modular robot manipulators with uncertain environments

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Neural Computing and Applications 2025年第3期37卷 1617-1631页

作者： Dong, Bo Wang, Yuge An, Tianjiao Cui, Yiming Zhu, Xinye Department of Control Science and Engineering Changchun University of Technology Changchun130012 China

Modular robot manipulators (MRMs) based on harmonic drive (HD) transmissions perform various target tasks in unknown environments, and the main challenge is to overcome the uncertain noise and controller errors of systems generated by device vibrations while facing with unknown external disturbance. To address these challenges, a variational Bayesian (VB)-based extended Kalman filter (VBEKF) is developed as part of the MRM dynamic model to mitigate bias in torque estimation resulting from external interference within HD model joints. Furthermore, leveraging a two-player zero-sum game strategy, a robust adaptive dynamic programming (ADP) method based on single critic neural network (NN) is formulated to solve the Hamilton–Jacobi–Isaacs (HJI) equation in H∞ control problem, ultimately yielding an approximate optimal solution for H∞ control. The Lyapunov theory guarantees that the trajectory tracking error of a closed-loop MRM system remains ultimately uniformly bounded (UUB), even in the presence of unknown environmental disturbances. Ultimately, the experiment results are given to illustrate the advantages and effectiveness of the proposed method. The experimental results show that the proposed method reduces the control torque error by ∼20% compared with the existing control methods. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Extended Kalman filters

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Open-source dataset for traffic light and countdown display detection in urban environment

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science China(Information sciences) 2025年第5期68卷 407-408页

作者： Shuchun WAN Haitao DING Jianwei ZHANG Yunfeng HU Hong CHEN State Key Laboratory of Automotive Simulation and Control Jilin University Department of Control Science and Engineering Jilin University College of Electronic and Information Engineering Tongji University

Here we introduce an open-source dataset for traffic light and countdown display detection,which includes three subsets:a subset of traffic light data,a subset of traffic light and countdown display data,and a subset ...

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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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Comparison of the feedback linearization plus LQR controller and the PID controller for greenhouse indoor climate

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International Journal of Agricultural and Biological engineering 2025年第1期18卷 74-82页

作者： Kidist Ameha Mengesha Gang-Gyoo Jin Yung-Deug Son Department of Electrical Power and Control Engineering Adama Science and Technology UniversityAdama 888Ethiopia Department of Mechanical Facility Control Engineering Korea University of Technology and EducationChungnam 31253Republic of Korea

Greenhouse environmental control systems can improve the growth and quality of the plants within greenhouses by keeping a constant *** climate is a multi-input multi-output system that is significantly affected by climate factors like temperature,relative humidity,and carbon dioxide *** to the nonlinearity and existence of coupling among climate factors,the designed controller should provide good control *** study proposed both the feedback linearization plus linear quadratic regulator(LQR)controller and the proportional-integral-derivative(PID)controller for indoor air temperature and humidity control of a greenhouse *** nonlinear greenhouse model was transformed into its equivalent linear form using input-output feedback ***,a proportional-integral type LQR controller was designed for the linear form to achieve the overall nonlinear feedback control *** addition,the practical PID controller was designed and its gains were tuned using a genetic algorithm by considering the integral of absolute error and control deviation,and the integral of squared error and control deviation.A set of simulation works done on the nonlinear model illustrates the effectiveness of the two control *** control methods,feedback linearization plus LQR and PID,demonstrated effective performance in both setpoint tracking and disturbance *** feedback linearization plus LQR controller exhibited superior disturbance rejection capabilities,characterized by reduced perturbation peaks and faster recovery ***,the PID controller demonstrated superior setpoint tracking performance with minimal overshoot.

关键词： greenhouse climate control feedback linearization plus LQR control PID control genetic algorithm

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AdapSafe2: Prior-Free Safe-Certified Reinforcement Learning for Multi-Area Frequency control

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IEEE Transactions on Power Systems 2025年第3期40卷 2244-2257页

作者： Wan, Xu Sun, Mingyang Zhejiang University Department of Control Science and Engineering Hangzhou310058 China Peking University College of Engineering Beijing100871 China

Safe Reinforcement Learning (RL) has been widely investigated to conduct power systems frequency control under high renewable energy resources penetration. Nevertheless, existing safe RL-based frequency control methods still face two fundamental challenges to achieving safety guarantees: (1) operating in non-stationary environments without the prior knowledge of the system parameters and (2) simultaneously satisfying high-dimensional and time-varying safety constraints in multi-area cases. To this end, this paper proposes a prior-free reinforcement learning-based frequency control method with guaranteed safety for multi-area power systems named AdapSafe2. To tackle Challenge (1), a meta-based environmental learning algorithm is developed to automatically capture and rapidly adapts to non-stationary system parameters without relying on a predefined nominal model. Furthermore, a meta-RL framework is established to achieve a self-adaptive frequency control strategy without prior knowledge. Moreover, for Challenge (2), a novel safety-critic network and a safe-certified compensator based on the control barrier function are designed to identify time-varying safety constraints. Leveraging risk assessments from the safety-critic network, the compensator performs dynamic safety compensations only for areas with risk, thereby enhancing the efficiency of solving under high-dimensional safety constraints. Numerical simulations conducted under 2-Area and 3-Area wind-aggregated low-inertia power systems demonstrate that the proposed AdapSafe2 can outperform the state-of-the-art approaches while effectively satisfying the dynamic safety constraints. © 1969-2012 IEEE.

关键词： Renewable energy

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