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Embedding prescribed-time adaptive control protocol unveiling distributed consensus in multirobot systems via directed topology

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Science China(Information Sciences) 2025年第2期68卷 383-384页

作者： Yonghao XIE Xinru MA Hengyu LI Shaorong XIE School of Computer Engineering and Science Shanghai University School of Mechatronic Engineering and Automation Shanghai University

Recently, multirobot systems(MRSs) have found extensive applications across various domains, including industrial manufacturing, collaborative formation of unmanned equipment, emergency disaster relief, and war scenarios [1]. These advancements are largely supported by the development of consistency control theory. However, traditional dynamicsfree models may cause instability in complex robotic systems. Lagrangian dynamics offers a better approach for modeling these systems, as it facilitates controller design and optimization analysis. Despite this, challenges persist with unknown parameters and nonlinear friction within the systems.

关键词： Microrobots

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High-dimensional Steady-state Security Region Boundary Approximation in Power Systems Using Feature Non-linear Converter and Improved Oblique Decision Tree

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Journal of Modern Power Systems and Clean Energy 2024年第6期12卷 1786-1797页

作者： Yuxin Dai Jun Zhang Peidong Xu Tianlu Gao David Wenzhong Gao School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Department of Electrical and Computer Engineering DenverUSA

The steady-state security region(SSR)offers ro-bust support for the security assessment and control of new power systems with high uncertainty and ***,accurately solving the steady-state security region boundary(SS-RB),which is high-dimensional,non-convex,and non-linear,presents a significant *** address this problem,this paper proposes a method for approximating the SSRB in power systems using the feature non-linear converter and improved oblique decision ***,to better characterize the SSRB,boundary samples are generated using the proposed sampling *** samples are distributed within a limited distance near the ***,to handle the high-dimensionality,non-convexity and non-linearity of the SSRB,boundary samples are converted from the original power injection space to a new fea-ture space using the designed feature non-linear ***-sequently,in this feature space,boundary samples are linearly separated using the proposed information gain rate based weighted oblique decision ***,the effectiveness and generality of the proposed sampling method are verified on the WECC 3-machine 9-bus system and IEEE 118-bus system.

关键词： Steady-state security region boundary sample generation feature non-linear conversion oblique decision tree

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Secure signal and image transmissions using chaotic synchronization scheme under cyber-attack in the communication channel

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Soft Computing 2025年第1期29卷 339-353页

作者： Nobakht, Shaghayegh Ahmadi, Ali-Akbar Industrial Automation Laboratory Electrical and Computer Engineering Department Kharazmi University Tehran Iran

In this paper, problem of secure message (signal and image) transmission is studied. The message is encrypted by masking it with a chaotic system state and then transmitted to receiver-side via a communication channel. It is assumed that the communication channel may be prone to a cyber-attack. The transmission system dynamics in presence of the cyber-attack in the communication channel is modeled by a singular dynamical system. Then, at the receiver-side, a novel observer is designed to recover the message together with the cyber-attack signal. Estimation of the cyber-attack is crucial for monitoring the communication channel and enable a network supervisor to mitigate the adverse consequences and make an appropriate strategy. It is assumed neither restrictions on the message nor on the cyber-attack signals. This makes the proposed scheme, the best solution in the real applications. Moreover, comparing to the existing methods which two public and private channels are required, only one communication channel is used in this paper for transmission the encrypted signal which results in a cheaper solution. Solving the optimization problem can be easily performed with the help of the existing toolboxes such as YALMIP and CVX software in MATLAB. Finally, numerical simulations for signal and image transmission are presented to justify the applicability and superior performance of the proposed scheme. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Cyber attacks

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Adaptive coupled-sliding-variable-based finite-time control of composite formation for multi-robot systems

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Science China(Information Sciences) 2024年第10期67卷 244-260页

作者： Xinru MA Hengyu LI Jun LIU Yueying WANG Shaorong XIE Jun LUO School of Mechatronic Engineering and Automation Shanghai University School of Mathematics and Computer Application Technology Jining University School of Computer Science Shanghai University College of Mechanical and Vehicle Engineering Chongqing University

This paper focuses on the finite-time control(FTC) of the composite formation consensus(CFC)problems for multi-robot systems(MRSs). The CFC problems are firstly proposed for MRSs under the complex network topology of cooperative or cooperative-competitive networks. Regarding the problems of FTC and CFC on multiple Lagrange systems(MLSs), coupled sliding variables are introduced to deal with the robustness and consistent convergence. Then, the adaptive finite-time protocols are given based on the displacement approaches. With the premised FTC, tender-tracking methods are further developed for the problems of tracking information disparity. Stability analyses of those MLSs mentioned above are clarified with Lyapunov candidates considering the coupled sliding vectors, which provide new verification for tender-tracking systems. Under the given coupled-sliding-variable-based finite-time protocols, MLSs distributively adjust the local formation error to achieve global CFC and perform uniform convergence in time-varying tracking. Finally, simulation experiments are conducted while providing practical solutions for the theoretical results.

关键词： composite formation time-vary tracking information disparity tender-tracking finite-time control nonlinear robots complex networks symmetry consensus

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A Transfer Learning Framework for Deep Multi-Agent Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2346-2348页

作者： Yi Liu Xiang Wu Yuming Bo Jiacun Wang Lifeng Ma the School of Automation Nanjing University of Science and Technology the Department of Computer Science and Software Engineering Monmouth University

Dear Editor,This letter presents a new transfer learning framework for the deep multi-agent reinforcement learning(DMARL) to reduce the convergence difficulty and training time when applying DMARL to a new scenario [1... 详细信息

关键词： Deep agent Framework

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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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Coordinated Frequency Control for Isolated Power Systems with High Penetration of DFIG-Based Wind Power

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CSEE Journal of Power and Energy Systems 2024年第4期10卷 1399-1414页

作者： Xin Ding Wei Lin Jian Xu Yuanzhang Sun Liangzhong Yao Beilin Mao School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China Department of Electrical Engineering and Computer Science Case Western Reserve UniversityClevelandOH 44106 USA

This paper proposes a coordinated frequency control scheme for emergency frequency regulation of isolated power systems with a high penetration of wind *** proposed frequency control strategy is based on the novel nonlinear regulator theory,which takes advantage of nonlinearity of doubly fed induction generators(DFIGs)and generators to regulate the frequency of the power *** deviations and power imbalances are used to design nonlinear feedback controllers that achieve the reserve power distribution between generators and DFIGs,in various wind speed *** effectiveness and dynamic performance of the proposed nonlinear coordinated frequency control method are validated through simulations in an actual isolated power grid.

关键词： Frequency control isolated power systems nonlinear feedback nonlinear regulator theory wind power

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OCRBench: on the hidden mystery of OCR in large multimodal models

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Science China(Information Sciences) 2024年第12期67卷 23-35页

作者： Yuliang LIU Zhang LI Mingxin HUANG Biao YANG Wenwen YU Chunyuan LI Xu-Cheng YIN Cheng-Lin LIU Lianwen JIN Xiang BAI School of Artificial Intelligence and Automation Huazhong University of Science and Technology School of Electronic and Information Engineering South China University of Technology Microsoft Research School of Computer & Communication Engineering University of Science and Technology Beijing Institute of Automation Chinese Academy of Sciences School of Software Engineering Huazhong University of Science and Technology

Large models have recently played a dominant role in natural language processing and multimodal vision-language learning. However, their effectiveness in text-related visual tasks remains relatively unexplored. In this paper, we conducted a comprehensive evaluation of large multimodal models, such as GPT4V and Gemini, in various text-related visual tasks including text recognition, scene text-centric visual question answering(VQA), document-oriented VQA, key information extraction(KIE), and handwritten mathematical expression recognition(HMER). To facilitate the assessment of optical character recognition(OCR) capabilities in large multimodal models, we propose OCRBench, a comprehensive evaluation benchmark. OCRBench contains 29 datasets, making it the most comprehensive OCR evaluation benchmark available. Furthermore, our study reveals both the strengths and weaknesses of these models, particularly in handling multilingual text, handwritten text, non-semantic text, and mathematical expression *** importantly, the baseline results presented in this study could provide a foundational framework for the conception and assessment of innovative strategies targeted at enhancing zero-shot multimodal *** evaluation pipeline and benchmark are available at https://***/Yuliang-Liu/Multimodal OCR.

关键词： large multimodal model OCR text recognition scene text-centric VQA document-oriented VQA key information extraction handwritten mathematical expression recognition

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Multi-Occupancy Activity Recognition Based on Deep Learning Models Fusing UWB Localisation Heatmaps and Nearby-Sensor Interaction

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IEEE Internet of Things Journal 2025年第11期12卷 16037-16052页

作者： Anguita-Molina, Miguel Angel Cardoso, Pedro J. S. Rodrigues, Joao M. F. Medina-Quero, Javier Polo-Rodriguez, Aurora University of Granada Department of Computer Engineering Automation and Robotics 18071 Spain University of Algarve Nova Lincs and Institute of Engineering Faro8005-139 Portugal

Human Activity Recognition focuses on developing systems and techniques to recognise and categorise human actions automatically based on sensor data. This study combines ultra-wideband technology and binary sensors to describe and recognise daily activities in real-world environments with multiple occupants, ensuring accurate user localisation through non-invasive and privacy-respecting methods. A novel method that combines wearables with ultra-wideband technology, which allows the generation of heatmaps for accurate positioning, and binary sensors, which collect nearby interaction with daily activities in naturalistic conditions, is presented. A dataset comprised of real-world data collected from three individuals in a real-life environment (house) was compiled. Advanced deep learning models are implemented to effectively fuse spatiotemporal information, leading to an encouraging performance in recognition of daily activities. The promising results suggest that this approach could be viable for large-scale deployments in future smart environments. © 2014 IEEE.

关键词： Ultra-wideband (UWB)

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Recent advances of few-shot learning methods and applications

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Science China(Technological Sciences) 2023年第4期66卷 920-944页

作者： WANG JianYuan LIU KeXin ZHANG YuCheng LENG Biao LU JinHu School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China

The rapid development of deep learning provides great convenience for production and ***,the massive labels required for training models limits further ***-shot learning which can obtain a high-performance model by learning few samples in new tasks,providing a solution for many scenarios that lack *** paper summarizes few-shot learning algorithms in recent years and proposes a ***,we introduce the few-shot learning task and its ***,according to different implementation strategies,few-shot learning methods in recent years are divided into five categories,including data augmentation-based methods,metric learning-based methods,parameter optimization-based methods,external memory-based methods,and other ***,We investigate the application of few-shot learning methods and summarize them from three directions,including computer vision,human-machine language interaction,and robot ***,we analyze the existing few-shot learning methods by comparing evaluation results on mini Image Net,and summarize the whole paper.

关键词： few-shot learning deep learning meta learning data augmentation parameter optimization

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