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第42届中国控制会议

作者： Jiajun Chu Weihua Cao Chao Gan Yulong Yang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Deep-sea unmanned exploration equipment is an important tool for exploring and developing the resources in the ocean, and it can survey the deep-sea environment more visually with the help of visual images. However, the complex and variable environment and the low resolution of the underwater lens lead to the poor resolution of the images acquired by the equipment. In this paper, we propose a residual-dense connected method applied to unmanned deep-sea exploration equipment to improve it's image resolution. The method uses dense connections within the residual structure to improve the model detail information acquisition to ensure accuracy and model stability of ***, through the study of the model performance, a high precision residual-dense connected model with less computational effort is designed. Finally, the model is trained and tested using environmental images in deep-sea conditions, and it is demonstrated that the method can be applied to deep-sea unmanned exploration equipment for fast, accurate, and stable image super-resolution processing.

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Energy-aware Coverage Control of Multi-Agent systems with Control Barrier Function

Energy-aware Coverage Control of Multi-Agent Systems with Co...

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第42届中国控制会议

作者： Chengkai Qu Chao Zhai School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the *** order to improve the early warning of disasters, a persistent monitoring method of multi-agent systems is proposed in this *** ensure that the agent's energy is never exhausted, the set invariance constraint is included in the optimization problem. The goal is to minimize the difference between the actual control input of the robot and the nominal control input corresponding to the task to be performed. Moreover, the control barrier function(CBF) is used to transform the forward invariance of a subset of the robot state space into a control input constraint. The coverage control method in an uncertain environment is verified by numerical simulation. This work provides new insights into effective monitoring and early warning of geo-hazards.

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Optimal Carbon Capture,Utilization and Storage Planning for Multi-Energy System

Optimal Carbon Capture,Utilization and Storage Planning for ...

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第42届中国控制会议

作者： Aoyu Hu Da Xu Menglu Gao School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

In response to the national dual carbon policy,carbon capture,utilization and storage（CCUS） are currently attracting much *** paper proposes optimal CCUS planning for multi-energy *** this multi-energy system,transmission network and natural gas network are coupled via conversion and storage devices in the energy *** CCUS planning is formulated based on a source-sink matching method to analyze the CO capture points,CO storage points and CO transportation ***,the original CCUS planning problem is reformulated as a mixed integer second order cone programming（MISOCP） and subsequently solved to guarantee a satisfactory convergence *** studies on an urban multienergy system are implemented to verify the effectiveness and superiority of the proposed methodology over conventional scheme.

关键词： Networked system carbon reduction energy hub

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Zero-Shot Kidney Stone Segmentation Based on Segmentation Anything Model for Robotic-Assisted Endoscope Navigation 16th

Zero-Shot Kidney Stone Segmentation Based on Segmentation A...

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16th International Conference on intelligent Robotics and Applications, ICIRA 2023

作者： Meng, Hui Chen, Lingkai Zhu, Shiqiang Fei, Chentao Zhang, Yong Zheng, Miaojuan Han, Jianda Song, Wei School of Intelligent Science and Technology Hangzhou Institute for Advanced Study University of Chinese Academy of Sciences 1 Sub-lane Xiangshan Hangzhou310024 China Research Center for Intelligent Robotics Research Institute of Interdisciplinary Innovation Zhejiang Laboratory Hangzhou311100 China Hangzhou ElephantChain Network Technology Co. Ltd. Hangzhou China Faculty of Mechanical Engineering and Automation Zhejiang Sci-Tech University Hangzhou310018 China College of Artificial Intelligence and Tianjin Key Laboratory of Intelligent Robotics Institute of Robotics and Automatic Information Systems Nankai University Tianjin300350 China

ISBN: (纸本)9789819964888

Biomedical robotics has had a significant impact on flexible ureteroscopy (FURS) for the management of nephrolithiasis. The biomedical robots provide a suitable and safe platform for FURS. However, operating the robots expertly still represents a challenge for surgeons. Vision-based navigation is an effective means to simplify the operations of robots by surgeons, which has great potential to improve surgical efficiency. To achieve vision-based navigation, the localization of kidney stones in endoscopic images is the first step. In this paper, we propose a stone segmentation method (SSM) based on zero-shot learning, which consists of segmentation anything model (SAM), an image preprocessing module, and a mask postprocessing module. The SAM segments all objects in endoscopic images, which lack semantic information. The preprocessing module is designed to suppress interference of reflective area in endoscopic images, and the mask postprocessing module is used to filter noise masks. The experimental results on our collected endoscopic images indicate that our method achieves close accuracy on stone segmentation compared with supervised U-Net and VGG_U-Net, which significantly outperforms the Ostu and the SAM. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

关键词： Endoscopy

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Flexible Control Strategies with Current Limitation of VSI Under Unbalanced Grid Voltage Sags

Flexible Control Strategies with Current Limitation of VSI U...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Fathia Letaief Asma B. Rhouma Mahmoud Hamouda Université de Sousse Ecole Nationale d'Ingenieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Sousse Tunisia

The power injection from a distributed power generation system (DPGS) into the grid is commonly performed through a voltage-source inverter (VSI). However, under unbalanced grid faults, the VSI may disconnect from the grid, which leads to stability problems due to the lack of active power after the fault extinction. To enhance the inverter's fault ride through (FRT) capability i.e., it remains connected to the grid as requested by the grid codes, two flexible control strategies have been developed in the last years. They are named flexible oscillating-power control (FOPC) and voltage-support-oriented control (VSOC). This paper proposes generalized expressions of active and reactive powers' references under faulty conditions to satisfy the grid codes' requirements and limit the current injected by the inverter to the rated value. Numerical simulations are performed to evaluate the performances of the two flexible control strategies along with the proposed current limitation method.

关键词： Reactive power Simulation Power quality Power system stability Numerical simulation Inverters Stability analysis

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Model Predictive Control of Decomposition Furnace Based on Equivalent-Input-Disturbances

Model Predictive Control of Decomposition Furnace Based on E...

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Chinese Automation Congress (CAC)

作者： WeiKang Wu Gang Yu Wangyong He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geoscience Wuhan China Huaxin Cement Technology Management(Wuhan) Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the cement production process, the decomposer outlet temperature control faces challenges such as large time delay and multiple disturbances. A general control system cannot handle time delay and disturbances effectively at the same time. Therefore, in this paper, we consider the problem of disturbances in time-delay systems and suppress the disturbances present in the outlet temperature control of the decomposer by combining equivalent-input-disturbance (EID) and Model Predictive Control (MPC), where EID can estimate the disturbances and apply them to the input channels of the system, which do not require any information about the disturbances. Finally simulations are carried out in the catabolizer system and the results indicate that this system is able to suppress the perturbations effectively in time delay systems.

关键词： Delay effects Perturbation methods Optimal control Production Predictive models Aerospace electronics Mathematical models Temperature control State estimation Predictive control

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Reducing idleness in financial cloud services via multi-objective evolutionary reinforcement learning based load balancer

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Science China(Information Sciences) 2024年第2期67卷 20-40页

作者： Peng YANG Laoming ZHANG Haifeng LIU Guiying LI Department of Statistics and Data Science Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology Guangdong OPPO Mobile Telecommunications Corp. Ltd Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, without disconnecting them from the server side. This paper considers this need as a bi-objective online load balancing problem. A neural network based scalable policy is designed to route user requests to varied numbers of servers for the required elasticity. An evolutionary multi-objective training framework is proposed to optimize the weights of the policy. Not only is the new objective of idleness reduced by over 130% more than traditional industrial solutions, but the original load balancing objective itself is also slightly improved. Extensive simulations with both synthetic and real-world data help reveal the detailed applicability of the proposed method to the emergent problem of reducing idleness in financial services.

关键词： evolutionary reinforcement learning evolutionary multi-objective optimization load balance cloud computing

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H∞ consensus for stochastic Markov jump multi-agent systems with imperfect time-varying transition probabilities and multiplicative noise

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Applied Mathematics and Computation 2023年 436卷

作者： Wang, Jie Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China

In this paper, the H∞ consensus control problem for Markov jump multi-agent systems with imperfect time-varying transition probabilities is studied. Both the transition probability matrix and the higher-level transition probability matrix are considered to be partly unknown. What's more, the multiplicative noise is considered in the model to describe the factors from the changing environment. Sufficient conditions about state feedback controllers are derived by less linear matrix inequalities (LMIs) and are more convenient to program compared with the previous works. At last, the simulations are supplied to illustrate the effectiveness of the conclusions. © 2022

关键词： Multi agent systems

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Auto-Regressive with Exogenous Input Modelling Based Model Predictive Control of Cement Grate Cooler

Auto-Regressive with Exogenous Input Modelling Based Model P...

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Chinese Automation Congress (CAC)

作者： Tian Zhang Gang Yu Wangyong He Renjie Gui Weikang Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geoscience Wuhan China Huaxin Cement Technology Management(Wuhan) Wuhan China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

In the cement production process, the speed of grate coolers directly affects the residence time and cooling effect of cement clinker. Its effective control is of great significance to ensuring cement quality. But the adjustment of grate speed is a complex process, involving moderate cooling air, uniform clinker thickness, regulated output and other constraints. In this study, an Auto-Regressive with exogenous input (ARX) grate cooler prediction model is developed using a data-driven approach based on a company's cement production line, a model predictive control (MPC) approach is employed for the purpose of optimising the speed of the grate cooler based on the ARX model. The results demonstrate that the method of MPC exhibits greater stability than the method of PID, and that MPC technology has good efficacy and superiority in the adjustment of grate speed.

关键词： Kilns Cooling Cement industry Velocity control Production Switches Predictive models Control systems Stability analysis Predictive control

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Distributed Power Source Planning Based on Improved Particle Swarm Optimization

Distributed Power Source Planning Based on Improved Particle...

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Power and Electrical technology Conference (APET), Asia

作者： Jiahui Wang Zhili Tan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350367690

ISBN: (纸本)9798350367706

The multitude of advantages offered by distributed power generation units are recognized as crucial factors in enhancing the security of distribution networks. Ensuring the optimal size and placement of distributed generation (DG) units not only enhances system security but also increases profitability. Haphazard placement of DG units may lead to adverse impacts on the power system, resulting in increased power losses and diminished voltage distribution. Therefore, to ensure the optimal size and placement of DG units, this paper proposes a method to optimize DG scheduling and operation, thereby improving voltage distribution, reducing power losses, and enhancing the overall reliability of the entire grid. To reduce power loss (PL) and improve voltage distribution (VP), an adaptive chaotic particle swarm optimization (ACPSO) algorithm is employed to determine the optimal locations and sizes of DG units. By comparing this algorithm with traditional approaches, its efficacy in enhancing performance can be discerned.

关键词： Profitability Voltage Distributed power generation Power system reliability Planning Security Reliability Particle swarm optimization Optimization Testing

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