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arXiv 2022年

作者： Cheng, Bin Lv, Yuezu Li, Zhongkui Duan, Zhisheng Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201804 China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai200120 China Advanced Research Institute of Multidisciplinary Sciences Beijing Institute of Technology Beijing100081 China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314000 China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

This paper studies the consensus control problem faced with three essential demands, namely, discrete control updating for each agent, discrete-time communications among neighboring agents, and the fully distributed fashion of the controller implementation without requiring any global information of the whole network topology. Noting that the existing related results only meeting one or two demands at most are essentially not applicable, in this paper we establish a novel framework to solve the problem of fully distributed consensus with discrete communication and control. The first key point in this framework is the design of controllers that are only updated at discrete event instants and do not depend on global information by introducing time-varying gains inspired by the adaptive control technique. Another key point is the invention of novel dynamic triggering functions that are independent of relative information among neighboring agents. Under the established framework, we propose fully distributed state-feedback event-triggered protocols for undirected graphs and also further study the more complexed cases of output-feedback control and directed graphs. Finally, numerical examples are provided to verify the effectiveness of the proposed event-triggered protocols. Copyright © 2022, The Authors. All rights reserved.

关键词： Directed graphs

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Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions

arXiv

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arXiv 2020年

作者： Zardini, Gioele Lanzetti, Nicolas Censi, Andrea Frazzoli, Emilio Pavone, Marco Institute for Dynamic Systems and Control ETH Zürich Zürich Switzerland Automatic Control Laboratory ETH Zürich Zürich Switzerland Department of Aeronautics and Astronautics Stanford University StanfordCA United States

The design of future mobility solutions and the design of the mobility systems they enable are closely coupled. Indeed, knowledge about the intended service of novel mobility solutions would impact their design and deployment process, whilst insights about their technological development could significantly affect transportation management policies. This requires tools to study such a coupling and co-design mobility systems in terms of different objectives. We present a framework to address such co-design problems, leveraging a mathematical theory of co-design to frame and solve the problem of designing and deploying an intermodal mobility system, whereby autonomous vehicles service travel demands jointly with micromobility solutions and public transit, in terms of fleets sizing, vehicle characteristics, and public transit service frequency. Our framework is modular and compositional, allowing one to describe the design as the interconnection of simple components and to tackle it from a systemic perspective. Moreover, it requires general monotonicity assumptions and naturally handles multiple objectives, delivering rational, actionable solutions for policy makers. We showcase our methodology in a case study of Washington D.C., USA. Our work suggests the possibility to create user-friendly optimization tools to systematically assess costs and benefits of interventions, and to inform policy-making in the future. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

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Stability analysis of the observer error of an in-domain actuated vibrating string

arXiv

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arXiv 2020年

作者： Malzer, Tobias Rams, Hubert Kolar, Bernd Schöberl, Markus Institute of Automatic Control and Control Systems Technology Johannes Kepler University Linz Altenbergerstrasse 66 Linz4040 Austria B&R Industrial Automation GmbH B&R Straße 1 Eggelsberg5142 Austria

In this paper, the behaviour of the observer error of an in-domain actuated vibrating string, where the observer system has been designed based on energy considerations exploiting a port-Hamiltonian system representation for infinite-dimensional systems, is analysed. Thus, the observer-error dynamics are reformulated as an abstract Cauchy problem, which enables to draw conclusions regarding the well-posedness of the observer-error system. Furthermore, we show that the observer error is asymptotically stable by applying LaSalle's invariance principle for infinite-dimensional systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Hamiltonians

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An Adaptive Robust Event-Triggered Variational Bayesian Filtering Method with Heavy-Tailed Noise

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Sensors (Basel, Switzerland) 2025年第10期25卷 3130页

作者： Di Deng Peng Yi Junlin Xiong Department of Control Science and Engineering Tongji University Shanghai 201804 China. Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 201210 China. Department of Automation University of Science and Technology of China Hefei 230026 China.

Event-triggered state estimation has attracted significant attention due to the advantage of efficiently utilizing communication resources in wireless sensor networks. In this paper, an adaptive robust event-triggered variational Bayesian filtering method is designed for heavy-tailed noise with inaccurate nominal covariance matrices. The one-step state prediction probability density function and the measurement likelihood function are modeled as Student's t-distributions. By choosing inverse Wishart priors, the system state, the prediction error covariance, and the measurement noise covariance are jointly estimated based on the variational Bayesian inference and the fixed-point iteration. In the proposed filtering algorithm, the system states and the unknown covariances are adaptively updated by taking advantage of the event-triggered probabilistic information and the transmitted measurement data in the cases of non-transmission and transmission, respectively. The tracking simulations show that the proposed filtering method achieves good and robust estimation performance with low communication overhead.

关键词： event-triggered scheduling scheme non-Gaussian noise robust state estimation variational Bayesian approach

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Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Learning

Depth-Aware Multi-Modal Fusion for Generalized Zero-Shot Lea...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Weipeng Cao Xuyang Yao Zhiwu Xu Yinghui Pan Yixuan Sun Dachuan Li Bohua Qiu Muheng Wei Guangdong Laboratory of Artificial Intelligence and Digital Economy (Shenzhen) Shenzhen China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Stony Brook University New York United States Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China ZhenDui Industry Artificial Intelligence Co. Ltd Shenzhen China Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Realizing Generalized Zero-Shot Learning (GZSL) based on large models is emerging as a prevailing trend. However, most existing methods merely regard large models as black boxes, solely leveraging the features output by the final layer while disregarding potential performance enhancements from other layers. Indeed, numerous researchers have visually depicted variations in the features learned across different layers of neural networks. Motivated by this observation, we propose a Vision Transformer (ViT)-based GZSL method named Depth-Aware Multi-Modal ViT (DAM2ViT), which exploits multi-level features of ViT. DAM2ViT incorporates a multi-modal interaction block to align semantic information of categories across multiple layers, thereby augmenting the model's capacity to learn associations between visual and semantic spaces. Extensive experiments conducted on three benchmark datasets (i.e., CUB, SUN, AWA2) have showcased that DAM2ViT achieves competitive results compared to state-of-the-art methods.

关键词： Visualization Adaptation models Semantics Zero shot learning Neural networks Termination of employment Transformers Market research Sun Optimization

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Privacy Preservation for Cloud-Edge-Collaborative Energy Management System Using Post-Quantum Homomorphic Encryption

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IEEE Transactions on Smart Grid 2025年

作者： Jiang, Cheng Li, Xue Du, Dajun Qian, Hong Wen, Mi Wu, Lei Findeisen, Rolf Shanghai University of Electric Power Shanghai Key Laboratory of Power Station Automation Technology College of Automation Engineering Shanghai200090 China Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States TU Darmstadt Control and Cyber-Physical Systems Laboratory Darmstadt64227 Germany

Cloud-based energy management systems (EMS) in smart grids face privacy challenges, as existing methods based on traditional homomorphic encryption support limited operations and are vulnerable to quantum attacks. We propose a privacy preservation method for smart grid energy management system, leveraging edge-assisted computing and ring learning with errors (RLWE) homomorphic encryption. Our approach enables both addition and multiplication operations on encrypted smart grid data while defending against quantum threats. We demonstrate the methods security under the RLWE hardness assumption and validate its effectiveness through an experimental platform simulating smart grid environments. This work addresses computational limitations in current privacy-preserving techniques, enhancing data security for evolving smart grid technologies © 2010-2012 IEEE.

关键词： Power management (telecommunication)

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AirVista-II: An Agentic System for Embodied UAVs Toward Dynamic Scene Semantic Understanding

arXiv

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arXiv 2025年

作者： Lin, Fei Tian, Yonglin Zhang, Tengchao Huang, Jun Guan, Sangtian Wang, Fei-Yue Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology 999078 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Unmanned Aerial Vehicles (UAVs) are increasingly important in dynamic environments such as logistics transportation and disaster response. However, current tasks often rely on human operators to monitor aerial videos and make operational decisions. This mode of human-machine collaboration suffers from significant limitations in efficiency and adaptability. In this paper, we present AirVista-II—an end-to-end agentic system for embodied UAVs, designed to enable general-purpose semantic understanding and reasoning in dynamic scenes. The system integrates agent-based task identification and scheduling, multimodal perception mechanisms, and differentiated keyframe extraction strategies tailored for various temporal scenarios, enabling the efficient capture of critical scene information. Experimental results demonstrate that the proposed system achieves high-quality semantic understanding across diverse UAV-based dynamic scenarios under a zero-shot setting. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

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Development of a New Machine Learning-based Informatics System for Product Health Monitoring

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Procedia CIRP 2020年 93卷 473-478页

作者： Moschos Papananias Olusayo Obajemu Thomas E McLeay Mahdi Mahfouf Visakan Kadirkamanathan Department of Automatic Control and Systems Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK Sandvik Coromant Mossvägen 10 Sandviken 811 34 Sweden

Manufacturing informatics aims to optimize productivity by extracting information from numerous data sources and making decisions based on that information about the process and the parts being produced. Manufacturing processes usually include a series of costly operations such as heat treatment, machining, and inspection to produce high-quality parts. However, performing costly operations when the product conformance to specifications cannot be achievable is not desirable. This paper develops a new machine learning-based informatics system capable of predicting the end product quality so that non-value-adding operations such as inspection can be minimized and the process can be stopped before completion when the part being manufactured fails to meet the design specifications.

关键词： Manufacturing Informatics Multistage Manufacturing Process Principal Componet Analysis Artificial Neural Networks Multiple linear Regression

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Highly Efficient W18o49-Based Composites for the Photocatalytic Co2 Cycloaddition: An Economic and Ecofriendly Choice

SSRN

引用

SSRN 2022年

作者： Cheng, Ruolin Wang, Anhu Sang, Shuxun Liang, Huagen Liu, Shiqi Tsiakaras, Panagiotis Jiangsu Key Laboratory of Coal-based Greenhouse Gas Control and Utilization Carbon Neutrality Institute China University of Mining and Technology Jiangsu Xuzhou221008 China School of Materials Science and Physics China University of Mining and Technology Xuzhou221008 China Laboratory of Alternative Energy Conversion Systems Department of Mechanical Engineering School of Engineering University of Thessaly Pedion Areos 38834 Greece

Converting captured CO2 into chemical products and fuels with high-added value is a key technology to achieve carbon neutralization. The CO2 cycloaddition of epoxides is a highly attractive long-term carbon-fixation strategy, but harsh reaction conditions and expensive catalysts limit its industrial application. Herein, cheap and non-toxic non-stoichiometric tungsten oxide is introduced for first time as a catalyst for CO2 cycloaddition reaction of styrene oxide. More precisely, low-cost and highly efficient W18O49-based composites were constructed by in-situ solvothermal synthesis, among which the W18O49/g-C3N4 composites exhibited the highest yield of 74% (271mmolg-1h-1) in the probe-reaction of styrene carbonate production. The physicochemical characterizations indicate that the photocatalysis plays a fundamental role in this reaction by promoting the activation of CO2 and styrene oxide. The crucial role of photogenerated-electrons and Lewis acid-base sites are confirmed. In this work is presented, the selection of a novel catalyst able to produce cyclic carbonate under ambient conditions. © 2022, The Authors. All rights reserved.

关键词： Carbon dioxide

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Optimal model-based sensor placement and adaptive monitoring of an oil spill

arXiv

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arXiv 2019年

作者： Hodgson, Zak Esnaola, Iñaki Jones, Bryn Department of Automatic Control and Systems University of Sheffield Sheffield

This paper presents a model based adaptive monitoring method for the estimation of flow tracers, with application to mapping, prediction and observation of oil spills in the immediate aftermath of an incident. Autonomous agents are guided to optimal sensing locations via the solution of a PDE constrained optimisation problem, obtained using the adjoint method. The proposed method employs a dynamic model of the combined ocean and oil dynamics, with states that are updated in real-time using a Kalman filter that fuses agent-based measurements with a reduced-order model of the ocean circulation dynamics. In turn, the updated predictions from the fluid model are used to identify and update the reduced order model, in a process of continuous feedback. The proposed method exhibits a 30% oil presence mapping and prediction improvement compared to standard industrial oil observation sensor guidance and model use. Copyright © 2019, The Authors. All rights reserved.

关键词： Multi agent systems

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