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Stabilization of nonlinear safety-critical systems by relaxed converse Lyapunov-barrier approach and its applications in robotic systems

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Autonomous Intelligent systems 2024年第1期4卷 73-80页

作者： Haoqi Li Jiangping Hu Xiaoming Hu Bijoy K.Ghosh School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu611731China Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313000China Optimization and Systems Theory Royal Institute of TechnologyStockholmSE-10044Sweden Department of Mathematics and Statistics Texas Tech UniversityLubbock79409-1042TXUSA

Combining safety objectives with stability objectives is crucial for safety-critical *** studies generally unified these two objectives by constructing Lyapunov-type barrier ***,insufficient analysis of key set relationships within the system may render the proposed safety and stability conditions conservative,and these studies also did not provide how to use such conditions to design safety-stability control *** paper proposed a feasible and constructive design to achieve stabilization of safety-critical systems by a relaxed converse Lyapunov-barrier *** analyzing the relationships between a series of sets associated with the safety-critical system,the stability and safety conditions can be appropriately ***,with the help of relaxed converse control Lyapunov-barrier functions(RCCLBFs),a theoretical result was obtained for the stability of affine nonlinear systems with safety ***,a constructive method was developed for a second-order strict-feedback system to transform the process of solving RCCLBFs into a Lyapunov-like stabilization ***,the proposed safety-stability control method is exerted on a robotic system and demonstrated by simulations.

关键词： Lyapunov functions Barrier functions Safety Stability

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Non-Line-of-Sight Multipath Classification Method for BDS Using Convolutional Sparse Autoencoder with LSTM

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Tsinghua Science and technology 2025年第1期30卷 68-86页

作者： Yahang Qin Zhenni Li Shengli Xie Bo Li Ming Liu Victor Kuzin School of Automation Guangdong University of Technologyand also with Guangdong-Hong Kong-Macao Joint Laboratory for Smart Discrete ManufacturingGuangzhou 510006China School of Automation Guangdong University of TechnologyGuangdong Key Laboratory of IoT Information TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Key Laboratory of Intelligent Information Processing and System Integration of IoTMinistry of EducationGuangzhou 510006China Department of Electronic and Computer Engineering Hong Kong University of Science and TechnologHong Kong 999077China Academician of Russian Engineering Academy Moscow Moscow 125009Russia

Multipath signal recognition is crucial to the ability to provide high-precision absolute-position services by the BeiDou Navigation Satellite system(BDS).However,most existing approaches to this issue involve supervised machine learning(ML)methods,and it is difficult to move to unsupervised multipath signal recognition because of the limitations in signal *** by an autoencoder with powerful unsupervised feature extraction,we propose a new deep learning(DL)model for BDS signal recognition that places a long short-term memory(LSTM)module in series with a convolutional sparse autoencoder to create a new autoencoder ***,we propose to capture the temporal correlations in long-duration BeiDou satellite time-series signals by using the LSTM module to mine the temporal change patterns in the time ***,we develop a convolutional sparse autoencoder method that learns a compressed representation of the input data,which then enables downscaled and unsupervised feature extraction from long-duration BeiDou satellite series ***,we add an l_(1/2) regularizer to the objective function of our DL model to remove redundant neurons from the neural network while ensuring recognition *** tested our proposed approach on a real urban canyon dataset,and the results demonstrated that our algorithm could achieve better classification performance than two ML-based methods(e.g.,11%better than a support vector machine)and two existing DL-based methods(e.g.,7.26%better than convolutional neural networks).

关键词： convolutional sparse autoencoder BeiDou Navigation Satellite system(BDS) long short-term memory(LSTM) multipath classification

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Exploring Eye-Tracking Based Biomarkers to Assess Cognitive Abilities in Autistic Children: A Feasibility Study

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IEEE Journal of Biomedical and Health Informatics 2025年第6期29卷 4401-4414页

作者： Zhang, Hanlin Hu, Chunchun Wang, Zhiyong Zhou, Bingrui Wang, Xinming Nie, Wei Ye, Qinyi Lin, Ruihan Xu, Xiu Liu, Honghai Harbin Institute of Technology State Key Laboratory of Robotics and System School of Mechanical Engineering and Automation Shenzhen518055 China Children's Hospital of Fudan University Department of Child Health Care Shanghai201102 China Peng Cheng Laboratory Shenzhen518000 China

Cognitive assessment can reveal a person's cognitive processing and behavioral patterns, making it an indispensable component of autism intervention and prognosis. Existing machine-assisted cognitive assessment methods primarily focus on children's performance outcomes, overlooking distinctive behavioral models, particularly characteristics of eye movement behavior, which have been demonstrated as the most direct indicators of cognitive abilities. In this study, we explore eye-tracking biomarkers for assisting cognitive assessment through a series of meticulously designed multi-level human-computer interaction protocols, encompassing three cognitive abilities: pairing and categorization, emotion recognition, and social interaction. A platform embedded with an eye-tracking module has been developed to reliably collect and analyze eye movement data, even in the presence of unrestricted large head movements in children. Experimental results indicate that there are significant group differences between autism and typically developing children in the eye-tracking features of total fixation duration, response latency, time to first fixation, mean fixation duration, and visit count in the absence of significant intergroup differences in the Wechsler Preschool and Primary Scale of Intelligence (WPPSI) and Wechsler Intelligence Scale for Children (WISC) assessment results. In addition, certain eye-tracking features in each group are correlated with WPPSI/WISC scale scores, enabling clinical cognitive assessments within each group based on these eye movement features. This study suggests that using eye-tracking features as biomarkers to assist detailed cognitive assessments holds significant potential for the intervention and prognosis of autism. © 2013 IEEE.

关键词： Diseases

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Attention-Based Multiagent Graph Reinforcement Learning for Service Restoration

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第5期5卷 2163-2178页

作者： Fan, Bangji Liu, Xinghua Xiao, Gaoxi Kang, Yu Wang, Dianhui Wang, Peng Xi'an University of Technology School of Electrical Engineering Xi'an710048 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore University of Science and Technology of China Department of Automation School of Information Science and Technology Hefei230027 China China University of Mining and Technology Artificial Intelligence Research Institute Xuzhou221116 China Northeastern University State Key Laboratory of Integrated Automation for Process Industry Shenyang110819 China

With the ongoing integration of distributed energy resources, modern distribution systems are getting sufficient generation capacity to perform active restoration after outages without transmission system support. The model-based approaches are widely used in resolving service restoration problems, relying on accurate system models. Deep reinforcement learning is believed as an alternative solution for problem solving, although it has not been sufficiently explored. In this article, the service restoration process is described as a partially observable Markov decision process and a multiagent graph reinforcement learning approach based on attention is proposed to train multiple agents to coachieve the restoration goal to reinforce the system resilience in coping with extreme events. To consider the connections and correlations between nodes during the service restoration, the state of the active distribution network is defined by graph data that contains features of both topology and nodes. The perceived ability of the agents is empowered by graph convolutional networks during the feature extraction, supplying agents with more comprehensive data to learn more reasonable restoration strategies. In addition, the centralized training with attention is developed for multiagent systems, focusing on the relations between the agents to strengthen the teamwork capability. The performance of the proposed method is verified by a set of comparative studies on the IEEE-118 system with dispatchable generators, rooftop photovoltaics, and energy storage systems simultaneously. © 2023 IEEE.

关键词： Reinforcement learning

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Solving Orienteering Problems by Hybridizing Evolutionary Algorithm and Deep Reinforcement Learning

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5493-5508页

作者： Wang, Rui Liu, Wei Li, Kaiwen Zhang, Tao Wang, Ling Xu, Xin National University of Defense Technology College of System Engineering Changsha410073 China Xiangjiang Laboratory Changsha410205 China Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology HKL-MSI2T Changsha410073 China Tsinghua University Department of Automation Beijing100084 China National University of Defense Technology College of Intelligence Science and Technology Changsha410073 China

The orienteering problem (OP) is widely applied in real life. However, as the scale of real-world problem scenarios grows quickly, traditional exact, heuristics, and learning-based methods have difficulty balancing optimization accuracy and efficiency. This study proposes a problem decomposition-based double-layer optimization framework named DEA-DYPN to solve OPs. Using a diversity evolutionary algorithm (DEA) as the external optimizer and a dynamic pointer network (DYPN) as the inner optimizer, we significantly reduce the difficulty of solving large-scale OPs. Several targeted optimization operators are innovatively designed for stronger search ability, including a greedy population initialization heuristic, an elite strategy, a population restart mechanism, and a fitness-sharing selection strategy. Moreover, a dynamic embedding mechanism is introduced to DYPN to improve its characteristic learning ability. Extensive comparative experiments on OP instances with sizes from 20 to 500 are conducted for algorithmic performance validation. More experiments and analyses, including the significance test, stability analysis, complexity analysis, sensitivity analysis, and ablation experiments, are also conducted for comprehensive algorithmic evaluation. Experimental results show that our proposed DEA-DYPN ranks first according to the Friedman test and outperforms the competitor algorithms by 69%. © 2024 IEEE.

关键词： Evolutionary algorithms

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Predefined-Time Tracking Control of Second-Order Multi-agent systems with State Constraints 2

Predefined-Time Tracking Control of Second-Order Multi-agent...

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2nd International Conference on Mechatronics, Control and Robotics, ICMCR 2024

作者： Guo, Chaoqun Hu, Jiangping Park, Ju H. Kumar Ghosh, Bijoy University of Electronic Science and Technology of China School of Automation Engineering Chengdu China Yeungnam University Department of Electrical Engineering Gyeongsan Korea Republic of Texas Tech University Department of Mathematics and Statistics Lubbock United States

ISBN: (纸本)9798350396096

The predefined-time tracking control of an uncertain second-order multi-agent system is studied in this paper. To tackle both the unconstrained and constrained situations simultaneously, a uniform nonlinear transformation function is proposed. In addition, a time base generator (TBG) function is constructed to facilitate designing a predefined-time control. Moreover, to simplify the computational complexity of the controller design, a predefined-time characteristic filter is proposed by utilizing the TBG function. And also based on the TBG function, an adaptive law is developed to estimate the unknown norms of the fuzzy weights. Consequently, a predefined-time tracking controller based on the TBG technique is designed to achieve the state constraints and consensus tracking. At last, to validate the predefined-time control strategy for the uncertain nonlinear multi-agent system, the simulations are presented. © 2024 IEEE.

关键词： Multi agent systems

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Performance Improvement of Poem Genre Classification using a Combination of SMOTE and Support Vector Machine

Performance Improvement of Poem Genre Classification using a...

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2023 International Seminar on Application for technology of Information and Communication, iSemantic 2023

作者： Aini, Quratu Muljono Yakub, Fitri Universitas Dian Nuswantoro Informatics Engineering Department Semarang Indonesia Malaysia-Japan International Institute of Technology Utm Electronic System Engineering Department Kuala Lumpur Malaysia

ISBN: (纸本)9798350339215

Text classification aims to be able to classify documents into the correct class. In this study, the use of SVM to perform text classification. The existence of this research is to find out how good the performance produced by SVM is in classifying text. A total of 841 poetry data were categorized into 4 genres namely affection, death, environment, and music. The data is cleaned at the text preprocessing stage with the stages of case folding (lowercase, remove punctuation and whitespace), tokenization, stopword removal, and lemmatizing. Feature extraction using Bag of Word (BoW) produces 6860 features. Features resulting from BoW will be weighted using TF - IDF. Data separation is carried out with a separation ratio of 80:20, 70:30, and 60:40. There is data imbalance, so it needs to be balanced. In this research, data balancing is done using SMOTE. Data separation is done for original data, balancing result data, and balancing result data with PCA. The highest accuracy result of train data is obtained by balancing data with a 60:40 separation of 97%. While the highest test data accuracy result is obtained by balancing data with an 80:20 separation of 87%. Thus the highest accuracy of each train data and test data is obtained by balancing data. © 2023 IEEE.

关键词： Support vector machines

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Transfer of 2D Films: From Imperfection to Perfection

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ACS Nano 2024年第23期18卷 14841-14876页

作者： Pham, Phuong V. Mai, The-Hung Dash, Saroj P. Biju, Vasudevanpillai Chueh, Yu-Lun Jariwala, Deep Tung, Vincent Department of Physics National Sun Yat-sen University Kaohsiung80424 Taiwan Department of Microtechnology and Nanoscience Chalmers University of Technology Gothenburg41296 Sweden Research Institute for Electronic Science Hokkaido University Hokkaido001-0020 Japan Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Department of Chemical System Engineering School of Engineering The University of Tokyo Tokyo113-8656 Japan

Atomically thin 2D films and their van der Waals heterostructures have demonstrated immense potential for breakthroughs and innovations in science and technology. Integrating 2D films into electronics and optoelectronics devices and their applications in electronics and optoelectronics can lead to improve device efficiencies and tunability. Consequently, there has been steady progress in large-area 2D films for both front- and back-end technologies, with a keen interest in optimizing different growth and synthetic techniques. Parallelly, a significant amount of attention has been directed toward efficient transfer techniques of 2D films on different substrates. Current methods for synthesizing 2D films often involve high-temperature synthesis, precursors, and growth stimulants with highly chemical reactivity. This limitation hinders the widespread applications of 2D films. As a result, reports concerning transfer strategies of 2D films from bare substrates to target substrates have proliferated, showcasing varying degrees of cleanliness, surface damage, and material uniformity. This review aims to evaluate, discuss, and provide an overview of the most advanced transfer methods to date, encompassing wet, dry, and quasi-dry transfer methods. The processes, mechanisms, and pros and cons of each transfer method are critically summarized. Furthermore, we discuss the feasibility of these 2D film transfer methods, concerning their applications in devices and various technology platforms. © 2024 The Authors. Published by American Chemical Society.

关键词： Chemical vapor deposition

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Photoacoustic tomography based on interference stimulated narrow-band ultrasound 7

Photoacoustic tomography based on interference stimulated na...

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7th International Symposium on Laser Ultrasonics and Advanced Sensing, LU 2024

作者： Ye, Jun Zhang, Yang Yan, Peng Tang, Zhongduo Ni, Bin Xu, Bin Liu, Xuefeng Mehmood, Muhammad Qasim Xiong, Jichuan School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China School of Electrical Engineering and Automation Luoyang Institute of Science and Technology Luoyang471023 China Electrical Engineering Department Information Technology University of the Punjab Lahore54000 Pakistan

Photoacoustic tomography (PAT) has emerged as a promising noninvasive imaging technology with significant potential for various clinical applications in medical settings. Traditionally, PAT utilizes a single laser beam to generate the excitation light (Wang & Hu, 2012). Nonetheless, this method often suffers from low signal-to-noise ratios (SNR) and poor image contrast due to environmental noise and other interfering factors. This paper introduces an interference laser excitation technique designed to focus the distribution of excitation light more effectively. By processing the signals generated by the interference, environmental noise can be effectively distinguished from the desired signal, thereby reducing its impact on image quality. The results demonstrate that this proposed method yields a more concentrated photoacoustic signal with high SNR after filtering and produces highly contrasted reconstructed images. This approach holds practical value and provides a novel excitation scheme for clinical photoacoustic tomography. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Laser excitation

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Finite-Time Sideslip Differentiator-Based LOS Guidance for Robust Path Following of Snake Robots

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IEEE/CAA Journal of Automatica Sinica 2023年第1期10卷 239-253页

作者： Yang Xiu Dongfang Li Miaomiao Zhang Hongbin Deng Rob Law Yun Huang Edmond Q.Wu Xin Xu the School of Mechatronical Engineering Beijing Institute of TechnologyBeijing 100081China the School of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Antai College of Economics&Management Shanghai Jiao Tong UniversityShanghai 200240China the Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China the Asia-Pacific Academy of Economics and Management University of MacaoMacao 999078China the Department of Decision Science Macao University of Science and TechnologyMacao 999078China the Department of Automation Shanghai Jiao Tong Universityand also with the Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai 200240China the College of Mechatronics and Automation National University of Defense TechnologyChangsha 410073China IEEE

This paper presents a finite-time sideslip differentiator-based line-of-sight(LOS)guidance method for robust path following of snake ***,finite-time stable sideslip differentiator and adaptive LOS guidance method are proposed to counteract sideslip drift caused by cross-track *** proposed differentiator can accurately observe the cross-track error and sideslip angle for snake robots to avoid errors caused by calculating sideslip angle *** our method,the designed piecewise auxiliary function guarantees the finite-time stability of position ***,for the case of external disturbances and state constraints,a Barrier Lyapunov functionbased backstepping adaptive path following controller is presented to improve the robot’s *** uniform ultimate boundedness of the closed-loop system is proved by analyzing ***,a gait frequency adjustment-based virtual velocity control input is derived to achieve the exponential convergence of the tangential *** last,the availability and superiority of this work are shown through simulation and experiment results.

关键词： Line-of-sight(LOS) path following sideslip snake robot

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