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第42届中国控制会议

作者： Tong Zhou Zhicheng Zhang Zhiqiang Zuo Yijing Wang Peng Li Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information EngineeringTianjin University Key Laboratory of System Control and Information Processing Ministry of Education

In this paper,component parameters of the boost converter are identified online using a multiple updating recursive least squares(MURLS) *** component parameters,such as resistance,inductor inductance and capacitor capacitance,are obtained directly through the identification procedure rather than transfer function *** MURLS algorithm is applied to improve the rapidity of system identification compared to the traditional recursive least squares(RLS) algorithm,which is verified by a comparative simulation between MURLS and RLS and the simulation of a load-switching scenario.

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Robust and Real-Time Road Edge Detection with Flexible LiDAR Configuration

Robust and Real-Time Road Edge Detection with Flexible LiDAR...

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Chinese control and Decision Conference, CCDC

作者： Jia-Chen Li Jun-Guo Lu Ming Wei Hong-Yi Kang Qing-Hao Zhang Key Laboratory of System Control and Information Shanghai Jiao Tong University Shanghai China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Road edge detection is an important component in autonomous driving for along-side scenarios. The road edge is defined as a boundary line where there is a height change from the road surface. However, the traditional LiDAR-based methods are not sensitive enough for small height difference. In addition, the point cloud needs to be provided in a channel-based organization, which means that at most one LiDAR’s data can be used for edge detection. In this paper, a novel road edge detection method is proposed to utilize flexible LiDAR configuration, e.g., multiple LiDARs. Specifically, the raw point cloud is first sorted in polar coordinates, and coarse edge points are generated according to height gradient for accurate ground segmentation. The non-ground points are further used to determine the road types based on occupancy map and beam models. The final edge points in the region of interest are extracted by dynamic slide window. Our method is evaluated on unmanned ground vehicle equipped with two Robosense LiDARs, and extensive experiments are conducted to demonstrate the effectiveness of our method.

关键词： Point cloud compression Laser radar Accuracy Roads Image edge detection Organizations Real-time systems

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State-of-Charge Balancing control for Battery Energy Storage systems of Near-Space Vehicles with An Electric-Thermal-Aging Coupling Model

State-of-Charge Balancing Control for Battery Energy Storage...

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第42届中国控制会议

作者： Zhiqiang Zuo Yunhao Du Yijing Wang Zhicheng Zhang Peng Li Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System School of Electrical and Information Engineering Tianjin University Key Laboratory of System Control and Information Processing Ministry of Education

State-of-charge(SoC) balancing is crucial for improving the efficiency and lifetime of the battery energy storage system in near-space vehicles. In this paper, the So C balancing control problem is investigated by a coupling battery model with electric-thermal-aging dynamics. Firstly, a system identification experiment is carried out to obtain the internal parameters of the battery. Secondly, a weight optimization index is designed by integrating the balancing speed and battery state-of-health(SoH). Then, a receding horizon control algorithm is proposed to realize multi-unit battery SoC balancing with partial swarm optimization(PSO). Finally, the effectiveness of the proposed strategy is verified by simulation results.

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A novel feature enhancement module for small object detection

A novel feature enhancement module for small object detectio...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Wang, Ruogu Li, Ning Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (纸本)9781728119489

Generic object detection has made great progress in recent years, yet small object detection is still facing a serious problem of missed detection. The problem is caused by two reasons: low resolution in small targets and feature loss during deep convolution downsampling. Some previous studies used feature pyramid structures and multi-scale training predictions to alleviate this problem, but still cannot efficiently utilise the feature information of small targets. In this paper, firstly we propose a novel and effective feature enhancement module to extract more features;secondly, a filter size design method is presented to extract features of matching objects and incorporate context information;finally, an adaptive fusion method is used to process outputs of our module and improve model robustness. We select YOLOv3 as base model and carry out several experiments on a special Small Object Dataset and the results show that our work can achieve an increase of about seven percentage points (35.73%) compared to 28.78% on baseline. © 2022 IEEE.

关键词： Object detection

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Model Predictive control Based on Amplitude Decaying Aggregation Strategy for Hydrogen Gas Turbine

Model Predictive Control Based on Amplitude Decaying Aggrega...

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2022 Chinese Automation Congress, CAC 2022

作者： Ma, Aoyun Li, Dewei Xi, Yugeng Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Key Laboratory of System Control and Information Processing Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781665465335

The hydrogen gas turbine can be the key technology for carbon-neutral in the future. The flexibility of gas turbine under various operation conditions is an important issue. A state-space model of hydrogen gas turbine with different hydrogen volume ratio mixed fuel is constructed based on Rowen model, and a full-dimensional state observer is designed to obtain the states of state-space model. The model predictive control method based on amplitude decaying aggregation strategy is presented to stabilize the rotational speed of hydrogen gas turbine under various constraints, which are to ensure the safety of operation. The number of variables contained in the optimization problem to be solved online is reduced by aggregation strategy. The simulation results confirmed that the presented method works well, and the effects of the hydrogen volume ratio for the performance of hydrogen gas turbine are discussed. © 2022 IEEE.

关键词： Model predictive control

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Online Learning Enabled Hierarchical Distributionally Robust Model Predictive control of Green-Hydrogen Microgrids under Uncertainties 5

Online Learning Enabled Hierarchical Distributionally Robust...

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5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Ning, Chao Li, Longyan Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

This paper proposes a novel online-learning enabled hierarchical operation framework for a green-hydrogen microgrid (MG) with a high penetration of renewable energy (RE) and hybrid energy storage. The operation framework features a bi-level multi-timescale structure which integrates a day-ahead optimal scheduling with online learning distributionally robust model predictive control (OL-DRMPC). Day-ahead scheduling optimization is employed at the high level to provide MG energy dispatch references, while the OL-DRMPC is carried out in the low level for reference-tracking under uncertainties incurred by RE and load forecast errors. To confront the imperfect knowledge of forecast-error distributions, distributionally robust conditional value-at-risk constraints are imposed on MG system states, namely the storage of battery and hydrogen, for a family of distributions called ambiguity set. By exploiting a Dirichlet process mixture model, a streaming-data-driven ambiguity set for uncertain parameters is devised over the runtime of controller and flexibly captures multimodal structure and fine-grained moment information of each mixture component. Enabled by online learning, the proposed strategy enjoys the merit of offering a reliable and intelligent MG operation. Case studies are used to demonstrate its effectiveness and superiority. © 2022 IEEE.

关键词： Energy storage

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Research summary of "Camellia oleifera fruit picking robot" technical analysis

Research summary of "Camellia oleifera fruit picking robot" ...

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2021 International Conference on Signal processing and Communication Technology, SPCT 2021

作者： Wang, Liang Hou, Yifeng Wang, Kuikui Wei, Chunming Guangxi Key Laboratory of Image Processing and Intelligent Information System Wuzhou University Wuzhou Guangxi543003 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

Aiming at the problems of my country's current camellia fruit picking mainly relying on manual picking, large labor and low efficiency, the development and promotion of camellia fruit picking equipment and technology are discussed, and technical analysis is carried out for the design of camellia fruit picking robots. This article analyzes the characteristics and existing problems of camellia fruit picking, and analyzes the four major components of the picking robot: "end effector", "manipulator motion control system", "visual recognition positioning system"and "driving walking device". In summary, summarize the problems that have been solved, the results achieved, and the difficulties that still exist, so as to provide enlightenment for the subsequent exploration of the subject research of "camellia fruit picking robot". © 2022 SPIE.

关键词： Fruits

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Integrated Power and Hydrogen Trading in Multimicrogrid Coupled with Offsite Hydrogen Refueling Stations 6

Integrated Power and Hydrogen Trading in Multimicrogrid Coup...

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6th IEEE Conference on Energy Internet and Energy system Integration, EI2 2022

作者： Li, Longyan Ning, Chao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9798350347159

This paper proposes a novel two-level electricity and hydrogen market framework for multi-microgrids (MMGs) coupled with offsite hydrogen refueling stations (HRSs), aiming to strengthen the synergy between electricity and hydrogen. The local hydrogen market among the MMG and HRSs is modeled by multi-leader multi-follower Stackelberg game theory, in which microgrids play the role of leaders to adjust hydrogen prices while HRSs participate as followers to determine their hydrogen purchase scheme. Moreover, to deal with economic and technical issues of the MMG in a holistic manner, Nash bargaining theory is used to model the electricity transaction among microgrids. A distributed algorithm is developed to solve such games, thus reducing the cost of information communication and the risk of privacy exposure. The case study demonstrates that this market mechanism guarantees benefits for all parties and boosts the independence of MMGs by reducing transactions with the main grid. © 2022 IEEE.

关键词： Game theory

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RRT Autonomous Detection Algorithm Based on Multiple Pilot Point Bias Strategy and Karto SLAM Algorithm

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Computers, Materials & Continua 2024年第2期78卷 2111-2136页

作者： Lieping Zhang Xiaoxu Shi Liu Tang Yilin Wang Jiansheng Peng Jianchu Zou Key Laboratory of Advanced Manufacturing and Automation Technology(Guilin University of Technology) Education Department of Guangxi Zhuang Autonomous RegionGuilin541006China College of Mechanical and Control Engineering Guilin University of TechnologyGuilin541006China Guilin Mingfu Robot Technology Company Limited Guilin541199China Key Laboratory of AI and Information Processing(Hechi University) Education Department of Guangxi Zhuang Autonomous RegionYizhou546300China

A Rapid-exploration Random Tree(RRT)autonomous detection algorithm based on the multi-guide-node deflection strategy and Karto Simultaneous Localization and Mapping(SLAM)algorithm was proposed to solve the problems of low efficiency of detecting frontier boundary points and drift distortion in the process of map building in the traditional RRT algorithm in the autonomous detection strategy of mobile ***,an RRT global frontier boundary point detection algorithm based on the multi-guide-node deflection strategy was put forward,which introduces the reference value of guide nodes’deflection probability into the random sampling function so that the global search tree can detect frontier boundary points towards the guide nodes according to random *** that,a new autonomous detection algorithm for mobile robots was proposed by combining the graph optimization-based Karto SLAM algorithm with the previously improved RRT *** algorithm simulation platform based on the Gazebo platform was *** simulation results show that compared with the traditional RRT algorithm,the proposed RRT autonomous detection algorithm can effectively reduce the time of autonomous detection,plan the length of detection trajectory under the condition of high average detection coverage,and complete the task of autonomous detection mapping more ***,with the help of the ROS-based mobile robot experimental platform,the performance of the proposed algorithm was verified in the real environment of different *** experimental results show that in the actual environment of simple and complex obstacles,the proposed RRT autonomous detection algorithm was superior to the traditional RRT autonomous detection algorithm in the time of detection,length of detection trajectory,and average coverage,thus improving the efficiency and accuracy of autonomous detection.

关键词： Autonomous detection RRT algorithm mobile robot ROS Karto SLAM algorithm

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An Expansion-based Document Ranking Framework Incorporated with Core Concern Capturing 5

An Expansion-based Document Ranking Framework Incorporated w...

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5th International Conference on Intelligent Autonomous systems, ICoIAS 2022

作者： Qi, Yinqiao Xin, Jinghao Li, Ning Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

Entity-based ranking is a popular research area in document ranking as knowledge graphs can introduce additional evidence for ranking systems. In most entity-based ranking framework, the original query is transformed into a set of entities and candidate documents are ranked according to their relevance to the entity set. However, mistakes can easily occur during the transformation process, which introduce noise to the ranking system. This paper represents an expansion-based ranking framework, which expand the original query with high-quality candidate entities to mitigate the impact of transformation mistakes and enrich the semantics of the query in the meanwhile. Compared with existing query expansion methods, our expansion method is lightweight as it reduces much computational burden and requests little extra information. However, the core concerns of the users might be covered up after query expansion. To alleviate this dilemma, a core concern capturing method is pro-posed, wherein the attention weight of each inter-entity relation is measured to capture the core entity pairs in the expanded query. Experiments on the S2-CS dataset demonstrate the effectiveness of our lightweight query expansion method and the superiority of our core concern capturing method. Compared with a classical retrieval model, our method provides 11% improvements in terms of NDCG@15. © 2022 IEEE.

关键词： Semantics

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