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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Cheng, Zikang Xue, Jingbo Wang, Bo Dong, Guangzhong Wei, Jingwen Chen, Chunlin Nanjing University Department of Control Science and Intelligence Engineering Naning China Harbin Institute of Technology Shenzhen School of Mechanical Engineering and Automation Shenzhen China

ISBN: (纸本)9798350366600

The Hybrid A∗ algorithm is suitable for Ackermann-type mobile robots with nonholonomic constraints. However, in practical path planning, such issues as long search times, inefficient search efficiency, and excessive planning path changes causing unstable robot motion still exist. To improve the effectiveness of path planning, this paper optimizes the Hybrid A∗ algorithm by using variable search step size and designing a path evaluation function during node expansion. Path planning experiments are conducted based on simulation and physical experimental platforms. The results show that the improved algorithm reduces the search nodes and planning time, effectively enhancing the algorithm's search performance and efficiency. In addition, it avoids pose errors caused by reverse driving, ensuring the priority and smoothness of forward driving, and achieves efficient and stable path planning for Ackermann-type mobile robots. © 2024 IEEE.

关键词： Mobile robots

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Multi-hypothesis Tracking Algorithm for Missile Group Targets

Multi-hypothesis Tracking Algorithm for Missile Group Target...

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2024 IEEE International Conference on Unmanned Systems, ICUS 2024

作者： Yang, Yueqi Yan, Tao Shen, Jiajie Sun, Guoqiang Tian, Zhenpo Ju, Wen School of Automation Science and Engineering Xi'an Jiaotong University Xi'an China Beijing Aerospace Automatic Control Institute Beijing China

ISBN: (纸本)9798350384185

This paper addresses the challenge of group targets tracking in complex environments, aiming to enhance the real-time performance and accuracy of tracking systems by optimizing multi-dimensional assignment strategy for selecting the globally optimal hypothesis. A new tracking algorithm named Ballistic Track-Oriented MHT (BTOMHT) is proposed. This algorithm introduces Lagrangian multipliers to achieve effective dimensionality reduction, thereby significantly decreases the computation complexity of data association in multi-dimensional spaces for group targets. Simulations demonstrate that compared with the Global Nearest Neighbor algorithm, BTOMHT not only sustains high precision but also has a great performance in complex dynamic tracking scenarios. It can enhance the efficiency of both target detection and tracking and concurrently bolster overall system stability in tracking tasks. The efficiency of the proposed algorithm is validated across two assessment indices. The algorithm contributes to the theoretical framework of multi-target tracking and furnishes technical support for applications in military defense. © 2024 IEEE.

关键词： Target tracking

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Investigating the impacts of spatial-temporal variation features of air density on assessing wind power generation and its fluctuation in China

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Science China(Technological Sciences) 2023年第6期66卷 1797-1814页

作者： REN GuoRui WANG Wei WAN Jie HONG Feng YANG Ke YU DaRen School of Control and Computer Engineering North China Electric Power UniversityBeijing 102206China School of Electrical Engineering and Automation Harbin Institute of TechnologyHarbin 150001China Xi’an Thermal Power Research Institute Co. Ltd.Xi’an 710054China School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China

Air density plays an important role in assessing wind *** density significantly fluctuates both spatially and *** literature typically used standard air density or local annual average air density to assess wind *** present study investigates the estimation errors of the potential and fluctuation of wind resource caused by neglecting the spatial-temporal variation features of air density in *** air density at 100 m height is accurately calculated by using air temperature,pressure,and *** spatial-temporal variation features of air density are firstly *** the wind power generation is modeled based on a 1.5 MW wind turbine model by using the actual air density,standard air densityρst,and local annual average air densityρsite,***ρstoverestimates the annual wind energy production(AEP)in 93.6%of the study *** significantly affects AEP in central and southern China *** more than 75%of the study area,the winter to summer differences in AEP are underestimated,but the intra-day peak-valley differences and fluctuation rate of wind power are ***ρsitesignificantly reduces the estimation error in *** AEP is still overestimated(0-8.6%)in summer and underestimated(0-11.2%)in *** for southwest China,it is hard to reduce the estimation errors of winter to summer differences in AEP by usingρ***ρsitedistinctly reduces the estimation errors of intra-day peak-valley differences and fluctuation rate of wind power,but these estimation errors cannot be ignored as *** impacts of air density on assessing wind resource are almost independent of the wind turbine types.

关键词： air density spatial-temporal variation power curve wind resource assessment fluctuation ERA-5

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Intelligent optimisation scheduling of raw material area in sausage production line

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International Journal of Simulation and Process Modelling 2023年第4期20卷 239-254页

作者： Han, Zhonghua Guan, Mingpeng Liu, Hangyu Chang, Daliang Sun, Liangliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110017 China School of Control Engineering Northeastern University at Qinhuangdao Hebei Qinhuangdao066099 China

The production process in the raw material area of the sausage production line needs to be further optimised to improve production efficiency and reduce the waiting time for suctioning of emulsifying fillings. In this study, we propose an improved Q-learning method for scheduling in raw material area (RMSPS-IQL). To overcome the problem of low learning efficiency caused by multi-operation and multi-tasking in the production line scheduling process, a priority stranding probability is added to the action selection method based on the epsilon-greedy strategy. In addition, to determine the execution time of the action during continuous working, a stranding action starting control method based on the probability of filling deterioration was designed. Comparative analysis of the results of multiple simulation schemes suggested that the RMSPS-IQL effectively reduces the waiting time for suctioning fillings from emulsifying pot, and improves the productivity of the production line. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Filling

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Digital Twin-Driven Degradation Modeling Method for control Moment Gyroscope Health Management 9

Digital Twin-Driven Degradation Modeling Method for Control ...

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9th IEEE International Conference on Big Data Computing Service and Applications, BigDataService 2023

作者： Cui, Runhao Huang, Xucong Zhang, Peng Tang, Diyin Beihang University School of Automation Science and Electrical Engineering Beijing China Beijing Institute of Control Engineering Beijing China

ISBN: (纸本)9798350333794

Prognosis and health management (PHM) of control moment gyroscope (CMG) plays a crucial role in ensuring the operational efficiency and safety of spacecraft. In order to improve the accuracy of PHM and supplement abundant monitoring data, this paper proposes a digital twin-driven degradation modeling method, which establishes a detailed simulation model based on degradation mechanisms at the CMG component level. The digital twin model not only provides a large amount of high-quality data for performance evaluation, but also serves as an important reference for on-orbit CMG state assessment. Finally, a case of estimating virtual sensor degradation information based on reinforcement learning is used to demonstrate the effectiveness of the proposed digital twin method. © 2023 IEEE.

关键词： Gyroscopes

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An Object-Oriented Model to Develop controllers of Autonomous Underwater Vehicles by Specializing the Unified Architecture Framework

An Object-Oriented Model to Develop Controllers of Autonomou...

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2024 International Conference on control, Robotics and Informatics, ICCRI 2024

作者： Cao, Duc Sang Ngo, Van Hien Le, Tran Thang Ngo, Van He Control Automation in Production and Improvement of Technology Institute Department of Electric Actuators & Automation Ha Noi Viet Nam Hanoi University of Science and Technology Department of Mechanical Engineering Ha Noi Viet Nam Control Automation in Production and Improvement of Technology Institute Department of Integrated System Ha Noi Viet Nam

ISBN: (纸本)9798350380309

Ocean engineering demands systemic solutions for mission-critical demands and technological challenges. From an industrial control perspective, development engineers need to factor in both costs and established standards to ensure the efficient implementation of the control system development lifecycle within a reasonable budget. Customization and reusability play key roles in driving down costs, resources, and development time when creating new applications. In the paper, the Unified Architecture Framework (UAF) [5], Model Based Systems engineering (MBSE), combined with real time Unified Modeling Language/Systems Modeling Language (UML/SysML) are merged and tailored to produce an object-oriented (OO) control model. This model is then extensively applied to develop a controller for Autonomous Underwater Vehicles (AUVs). To reach this objective, the dynamic model of an Autonomous Underwater Vehicle (AUV) are linked with specific specializations of UAF/MBSE. In this setup, the model of analysis is precisely outlined through the detailed description of a use case model, aimed at closely capturing the intricate control demands. The designed model is then specialized by using the real-time UML/SysML to retain key blocks, which are used to describe in detail structures for control and behaviors of AUV. Next, the designed model is transformed into the model of implementation via round-trip engineering, facilitating the quick realization of an AUV controller. Building upon this object-oriented model, a controller for course-tracking applied to a miniature AUV was designed. The results from the simulation demonstrate the good feasibility of the proposed model. © 2024 IEEE.

关键词： Budget control

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Predicting microbial extracellular electron transfer activity in paddy soils with soil physicochemical properties using machine learning

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Science China(Technological Sciences) 2024年第1期67卷 259-270页

作者： OU JiaJun LUO XiaoShan LIU JunYang HUANG LinYan ZHOU LiHua YUAN Yong School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control Guangzhou Key Laboratory Environmental Catalysis and Pollution ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China School of Biomedical and Pharmaceutical Sciences Guangdong University of TechnologyGuangzhou 510006China

Soil extracellular electron transfer(EET)is a pivotal biological process within the realm of ***,EET suffers from a lack of predictive ***,an intricately crafted machine learning model has been developed for the purpose of predicting soil EET by using the physicochemical properties of soil as independent input variables and the EET capabilities in terms of current density(j_(max))and Coulombic charge(C_(out))as dependent output *** autoencoder ensemble stacking(AES)model was developed to address the aforementioned issue by integrating support vector machine,multilayer perceptron,extreme gradient boosting,and light gradient boosting machine algorithms as the stacking *** 10-fold crossvalidation,the AES model exhibited notable improvements in predicting j_(max)and C_(out),with average test R^(2)values of 0.83 and 0.84,respectively,surpassing those of single machine learning(ML)models and the basic ensemble *** utilizing partial correlation plots(PDPs),Shapley Additive explanations(SHAP)values,and SHAP decision plots,we quantitatively explained the impact and contribution of the input molecules on the AES model’s predictions of j_(max)and C_(out).In the context of the SHAP method for the AES model,total carbon(TC)was identified as the most correlated descriptor for j_(max),while total organic carbon(TOC)stood out as the most relevant descriptor for C_(out).In the prediction tasks of j_(max)and C_(out)within the AES model,employing a multitask ML approach allowed the model to benefit from the shared information of input variables,thereby enhancing its overall *** study provides a feasible tool for the prediction of soil EET from soil physiochemical properties and an advanced understanding of the relationship between soil physiochemical properties and EET capability.

关键词： extracellular electron transfer paddy soil machine learning prediction autoencoder ensemble stacking model

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Research on LSTM-based winding state prediction method 7

Research on LSTM-based winding state prediction method

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2024 7th International Conference on Power Electronics and control engineering, ICPECE 2024

作者： Wang, Yiyang Guo, Haifeng Li, Jianan Liu, Xinen Li, Xiang Du, Zhongbo Shen, Yang School of Electrical and Automation Engineering Liaoning Institute of Science and Technology Benxi117004 China Liaoning Province Robot Drive Control Engineering Laboratory Benxi117004 China

Mechanical and electrical equipment is widely used in various links of the manufacturing industry and is also the key to the implementation of modern industrial technology. Winding is the core component of transformers, electromagnetic valves, motors, robots, and other mechanical and electrical equipment. The safe and reliable operation of winding is the premise for the healthy operation of industrial equipment. Therefore, taking the core component of many industrial equipment, the winding, as the research object, and aiming to improve the safety and reliability of the equipment, this study focuses on the state prediction method of winding with the help of sensitive feature information. With the rapid development of industrial big data technology, data-driven technology, especially time series prediction technology, has developed rapidly. Considering the characteristics of winding degradation data, a winding state prediction method based on the Long Short-Term Memory (LSTM) approach is proposed. By using experimental data of winding, a health index reflecting their health status is constructed, and the LSTM is utilized for training the health index, thereby achieving time series-based state prediction of winding. This provides reliable support for the health status assessment of industrial mechanical and electrical equipment and enhances the reliability of the equipment. © Published under licence by IOP Publishing Ltd.

关键词： Machine windings

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Combined Model-Compensated and Quasi-Resonant Linear Active Disturbance Rejection control for PMSM Drives

Combined Model-Compensated and Quasi-Resonant Linear Active ...

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2023 China automation Congress, CAC 2023

作者： Chen, Songtao Mao, Xuefei Zhao, Lei Wang, Shuoyu Zhang, Jiyang School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering Beijing100094 China

ISBN: (纸本)9798350303759

When operating at ultra-low speeds, Permanent Magnet Synchronous Motor (PMSM) is subject to disturbances such as non-linear frictional torque and periodic disturbance torque. These uncertain disturbances can cause fluctuations in speed, which deteriorate the speed loop performance. To address the problem, this paper proposed a linear active disturbance rejection control strategy (LADRC) that combined model-compensation and quasi-resonant control. The Stribeck model was chosen to estimate the non-linear frictional torque and input it into the linear expanding state observer (LESO) to reduce the estimation burden of LESO;The introduction of a quasi-resonant term (QR) in LESO improves the suppression of periodic harmonics in the mid-frequency band by linear active disturbance rejection control. Finally, the effectiveness of the proposed control strategy is verified by simulation experiments. © 2023 IEEE.

关键词： Friction

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Cognitive Navigation for Intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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