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

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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eVTOL Performance Analysis: A Review From control Perspectives

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-13页

作者： Su, Jiangcheng Huang, Hailong Zhang, Hong Wang, Yutong Wang, Fei-Yue Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic University Hong Kong China Co. Ltd. Guangzhou China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Electric Vertical Takeoff and Landing (eVTOL) aircraft has gained significant attention as a basic element of urban air mobility (UAM), a potential solution for urban transportation challenges using low-altitude urban airspace. Ensuring the safe operation of eVTOL is crucial for UAM applications, which are related to various professional fields such as aerodynamics, control, structures, and power systems. This article systematically analyzes the characteristics of different design configurations, including multi-rotor, lift+cruise, and tilt-rotor types of eVTOL. The advantages and limitations of each type of eVTOL are analyzed. After that, the overall design problems are analyzed, and challenges of eVTOL control system design are discussed from aspects of overall control structure and subsystems, such as controller, sensors, actuators, and command generator. This article tries to fill the gap in the eVTOL design from a control perspective and provides some resolutions for the eVTOL application. IEEE

关键词： Air mobility

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Psychomotor intervention through serious games in children and adolescents with autism spectrum disorder using a therapeutic robot

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Research on Biomedical engineering 2024年第3-4期40卷 485-497页

作者： da Luz Schreider, Sheila de Souza, Josiany Carlos da Silva Freitas, Éberte Valter Panceri, João Antonio Campos de Oliveira Caldeira, Eliete Maria Bastos-Filho, Teodiano Freire Av. Marechal Campos 1468 Maruipe Vitoria29047-105 Brazil Vitoria Brazil Vitoria Brazil Automation and Control Engineering Department Federal Institute of Espirito Santo Av. Filogônio Peixoto 2220 Aviso Linhares Brazil

Introduction: The autism spectrum disorder (ASD) is a neurodevelopmental disorder, characterized by an atypical neuropsychomotor development and communication. Methodology: In this work, a socially assistive robot termed MARIA T21 (Mobile Autonomous Robot for Interaction with Autistics and Trisomy 21) was used for interaction and application of serious games to children with ASD. The sample was composed of two groups: the first one with seven children with ASD, who had ten sessions with the robot at the Association of Friends of Autistics from Espirito Santo State (AMAES) in Vitoria, Brazil;and second group composed of four children with ASD, who had four sessions with the robot at the Association of Parents and Friends of Exceptional People (APAE) in Vila Velha, Brazil. The protocol was composed of four serious games, which stimulated postural balance, proprioception, and motor coordination. Results and conclusions: The utilization of the robot and serious games proved to be an important therapy tool, providing the children with playful activities, increasing their engagement, and providing them with a greater interaction between body and mind. In the evaluation of the psychomotor profile through the Psychomotor Battery by Victor da Fonseca, both groups had a statistically significant difference before and after the psychomotor intervention. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2024.

关键词： Serious games

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Learning Agile Quadrotor Flight in Restricted Environments with Safety Guarantees

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第9期9卷 1-8页

作者： Chen, Shiyu Li, Yanjie Lou, Yunjiang Lin, Ke Wu, Xinyu Department of Control Science and Engineering Harbin Institute of Technology Shenzhen and Guangdong Key Laboratory of Intelligent Morphing Mechanisms and Adaptive Robotics Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

With the increasing requirement for agile and efficient controllers in safety-critical scenarios, controllers that exhibit both agility and safety are attracting attention, especially in the aerial robotics domain. This paper focuses on the safety issue of Reinforcement Learning (RL)-based control for agile quadrotor flight in restricted environments. To this end, we propose a unified Adaptive Safety Predictive Corrector (ASPC) to certify each output action of the RL-based controller in real-time, ensuring its safety while maintaining agility. Specifically, we develop the ASPC as a finite-horizon optimal control problem, formulated by a variant of Model Predictive control (MPC). Given the safety constraints determined by the restricted environment, the objective of minimizing loss of agility can be optimized by reducing the difference between the actions of RL and ASPC. As the safety constraints are decoupled from the RL-based control policy, the ASPC is plug-and-play and can be incorporated into any potentially unsafe controllers. Furthermore, an online adaptive regulator is presented to adjust the safety bounds of the state constraints with respect to the environment changes, extending the proposed ASPC to different restricted environments. Finally, simulations and real-world experiments are demonstrated in various restricted environments to validate the effectiveness of the proposed ASPC. IEEE

关键词： Reinforcement learning

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Graph convolutional network soft sensor for process quality prediction

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Journal of Process control 2023年第1期123卷 12-25页

作者： Jia, Mingwei Xu, Danya Yang, Tao Liu, Yi Yao, Yuan Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Chemical Engineering National Tsing Hua University Hsinchu30013 Taiwan

The nonlinear time-varying characteristics of the process industry can be modeled using numerous data-driven soft sensor methods. However, the intrinsic relationships among the variables, especially the localized spatial–temporal correlations that shed light on model behavior, have received little attention. In this study, a soft sensor based on a graph convolutional network is constructed by introducing the concept of graph to process modeling. The focus is on obtaining localized spatial–temporal correlations that aid in comprehending the intricate interactions among the variables included in the soft sensor. The model is trained by considering the regularization terms and it learns distinctive localized spatial–temporal correlations in an end-to-end manner. Furthermore, long-term dependence is established via temporal convolution. Thus, both the localized spatial–temporal correlations and time-series properties are captured. The feasibility of the proposed soft sensor is illustrated using two fermentation processes. The localized spatial–temporal correlations of this case study are visualized, and they demonstrate that the soft sensor is not a black-box model;instead, it is consistent with process knowledge. © 2023 Elsevier Ltd

关键词： Convolution

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Latent-Enhanced Variational Adversarial Active Learning Assisted Soft Sensor

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IEEE Sensors Journal 2023年第14期23卷 15762-15772页

作者： Dai, Yun Yang, Chao Liu, Yi Yao, Yuan Zhejiang University of Technology Institute of Process Equipment and Control Engineering Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering Hsinchu300044 Taiwan

As the acquisition of variables that measure quality is typically challenging, labeled samples for building a model for soft sensors are often inadequate. Additionally, owing to the installation of redundant sensors, high-dimensional process data with strong correlations are acquired. Therefore, in this study, a sample selection strategy for active learning (AL), referred to as latent-enhanced variational adversarial AL (LVAAL), is developed to enhance quality prediction performance with limited labeled data. The LVAAL method uses a minimax game to explore the latent representation of the original data. Specifically, a latent-enhanced variational autoencoder (LEVAE) is used to deceive the adversarial network into predicting all samples, both labeled and unlabeled, as labeled. However, the adversarial network attempts to indicate the difference between latent representations. Subsequently, Gaussian process regression (GPR) is adopted as a base model for LVAAL. With the proposed LVAAL selection strategy, informative unlabeled samples are incrementally selected, thereby enhancing the prediction performance. The application results for a numerical case and an industrial example demonstrate the advantages of LVAAL compared with existing AL strategies. © 2001-2012 IEEE.

关键词： Gaussian distribution

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Development and control of Underwater Gliding Robots:A Review

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1543-1560页

作者： Jian Wang Zhengxing Wu Huijie Dong Min Tan Junzhi Yu the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China the State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking UniversityBeijing 100871China

As one of the most effective vehicles for ocean development and exploration,underwater gliding robots(UGRs)have the unique characteristics of low energy consumption and strong ***,by borrowing the motion principles of current underwater robots,a variety of novel UGRs have emerged with improving their maneuverability,concealment,and environmental friendliness,which significantly broadens the ocean *** this paper,we provide a comprehensive review of underwater gliding robots,including prototype design and their key *** the perspective of motion characteristics,we categorize the underwater gliding robots in terms of traditional underwater gliders(UGs),hybrid-driven UGs,bio-inspired UGs,thermal UGs,and ***,their buoyancy driven system,dynamic and energy model,and motion control are concluded with detailed ***,we have discussed the current critical issues and future *** review offers valuable insight into the development of next-generation underwater robots well-suited for various oceanic applications,and aims to gain more attention of researchers and engineers to this growing field.

关键词： Buoyancy driven motion control oceanic applications system development underwater gliding robots

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LI-DPS: A Long Sequence Dual Prediction Scheme Based on Informer for Efficient High-Frequency Data Transmission 50

LI-DPS: A Long Sequence Dual Prediction Scheme Based on Info...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Wu, Yu Yang, Bo Zhu, Dafeng Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9781665464543

High-frequency time-series data such as vibration signals will consume a lot of communication resources and require very high network bandwidth. Reducing the amount of data transmission while ensuring its availability is particularly important and challenging in high-frequency scenarios. Dual prediction scheme (DPS) can significantly reduce the amount of data transmission while ensuring data accuracy. However, traditional DPS cannot be applied to high-frequency scenarios due to the limitation of the mechanism design and model inference speed. We propose a novel long sequence DPS to efficiently reduce the volume of high-frequency data transmission in real time. To overcome the accuracy degradation due to gradient vanishing in long sequence prediction, we also propose an attention-based prediction model. Furthermore, we propose Informer to reduce the model’s computational complexity and enable fast inference and deployment on resource-constrained edge gateways. Experiments based on the real-world dataset show that the proposed scheme can efficiently cope with high-frequency data, reduce its transmission volume, and ensure data accuracy. © 2024 IEEE.

关键词： Prediction models

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Optimizing Hydrogen Highway Planning Model Considering Hydrogen Cost and Vehicle Flow Effects

Optimizing Hydrogen Highway Planning Model Considering Hydro...

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2024 IEEE IAS Industrial and Commercial Power system Asia, I and CPS Asia 2024

作者： Zhang, Yan Lv, Yong Wan, Yanming Sun, Yuxin Zhang, Xian Wang, Guibin Liu, Chang China Hydrogen Alliance Research Institute Beijing China Shenzhen University School of Mechanical Electrical and Control Engineering Shenzhen China University of Liverpool Department of Electrical and Electronic Engineering Liverpool United Kingdom School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350352290

In recent years, global governments have been actively advocating for the adoption of hydrogen fuel cell vehicles (HFCVs) as a means to foster a more sustainable future in transportation. However, the widespread integration of these vehicles necessitates robust hydrogenation infrastructure support. This paper presents a novel hydrogen highway optimization planning model tailored for the strategic placement of hydrogen refueling stations (HRSs) along highways. Based on the traditional HRS site selection models, this approach innovatively integrates factors encompassing hydrogen procurement, transportation, and utilization. The model optimizes the location, scale of the HRSs and quantity of hydrogen dispensers within each HRS, utilizing the minimum unit cost of hydrogen as the objective function. To verify the effectiveness, the proposed model is applied in the Beijing-Tianjin-Hebei (BTH) and Chongqing regions, conducting HRS location planning across both demonstration and promotion stages and the specific planning results are obtained. This study offers valuable insights into hydrogen infrastructure planning along highways, serving as a reference for future endeavors in this domain. © 2024 IEEE.

关键词： Hydrogen fuels

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RESEARCH ON DAMAGE LOCALIZATION TECHNIQUES FOR REUSABLE CARRIER TANK STRUCTURES

RESEARCH ON DAMAGE LOCALIZATION TECHNIQUES FOR REUSABLE CARR...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Ben, Xu Mei, Yuan Shaopeng, Dong Jiutian, Zhang Fuel System Department Nanjing Engineering Institute of Aircraft Systems AVIC Nanjing China School of Automation Science and Electrical Engineering Beihang University Beijing China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing China Ningho Institute of Technology Beihang University Ningbo China

Lamb waves, characterized by slow attenuation, short wavelength, and sensitivity to damage, have been widely utilized in the field of composite material damage detection. In addressing the issue of damage localization in composite curved tank structures, this study proposes a composite tank localization algorithm based on convolutional neural networks (CNNs) using Lamb wave data. The approach transforms the damage localization regression problem into a classification problem through partitioning, achieving damage zone localization in composite tank structures with fewer sensors. The accuracy of the algorithm is more than 98% in the dataset constructed from physical experiments, which verifies its accuracy and applicability. © The Institution of engineering & Technology 2024.

关键词： Tanks (containers)

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