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2024 IEEE International Conference on systems, Man, and Cybernetics, SMC 2024

作者： Miao, Zibo Pan, Yu Gao, Qing School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Guangdong Key Laboratory of Intelligent Morphing Mechanisms Shenzhen518055 China The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

ISBN: (纸本)9781665410205

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique. © 2024 IEEE.

关键词： Poles

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A Detector-Free Image Matching Method based on Enhanced Feature Fusion 43

A Detector-Free Image Matching Method based on Enhanced Feat...

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43rd Chinese control Conference, CCC 2024

作者： Chen, Ziyang Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Eduction Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

Image feature matching is an important research field in computer vision that can be widely applied to advanced vision tasks, such as 3D reconstruction and visual tracking. Considering the low matching accuracy and poor robustness of traditional detector-based matching methods on weakly textured images, we propose a detector-free image matching method based on enhanced feature fusion. Given that weak texture images consist of a large number of similar or irregular pixels, we introduce a new model that enhances feature fusion to recover the underlying texture information of the image. First, we propose a bidirectional fusion model to extract multi-scale feature maps and add an initialization module to correlate the feature maps and enhance the representation ability of the backbone. Then, we perform feature transformation using the quadtree attention model and finally establish dense pixel-by-pixel matching at both coarse and fine scales. The quadtree attention model employs a hierarchical computational attention method, accurately capturing image details and remote dependencies while ensuring linear complexity. Experimental results demonstrate that the proposed method achieves higher matching accuracy and better generalization on large datasets such as MegaDepth and ScanNet, making it suitable for subsequent work. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Image matching

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Integrated Prediction of Unfavorable Geology in Main Tunnel Considering the Geological Conditions of Parallel Tunnel

Integrated Prediction of Unfavorable Geology in Main Tunnel ...

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2024 China Automation Congress, CAC 2024

作者： Zhang, Meng Gan, Chao Cao, Weihua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

Currently, the advanced geological prediction for the main tunnel from the parallel tunnel often employs parallel deduction of detection conclusions, which faces issues such as a lack of diverse geological exploration information, a lack of analysis of geological structures and poor accuracy. In this paper, an integrated prediction method for unfavorable geology in main tunnel considering the geological conditions of parallel tunnel is proposed, which consists of three stages. In the first stage, based on the forecast mileage range and tunnel excavation conditions, the process is divided into four specific cases. In the second stage, it deduces the geology of the main tunnel along the orientation of rock strata occurrence or joint to parallel tunnel and selects the results of the rock strata occurrence or joint deduction according to the distance of the deduction. In the last stage, it deduces the geological conditions of parallel tunnel face and the integration of geophysical and drilling information for predictive conclusions based on the four specific cases. The proposed method offers higher prediction accuracy for rock mass integrity and surrounding rock grades compared to parallel deduction method. © 2024 IEEE.

关键词： Miocene

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Distributed Power Source Planning Based on Improved Particle Swarm Optimization 3

Distributed Power Source Planning Based on Improved Particle...

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3rd Asia Power and Electrical Technology Conference, APET 2024

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

ISBN: (纸本)9798350367690

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. © 2024 IEEE.

关键词： Power distribution planning

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Short-Term Load Forecasting Method Based on Multi-Branch Convolutional Network and Bayesian Optimization 43

Short-Term Load Forecasting Method Based on Multi-Branch Con...

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43rd Chinese control Conference, CCC 2024

作者： Lv, Ji Ding, Min Li, Quanhui Zhou, Sibei Fang, Zhijian China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Accurate short-term power load forecasting is important to ensure the reliability and economy of the power grid. Convolutional neural networks are widely used, but they are difficult to capture the multi-scale temporal characteristics of load data. To address this problem, this study proposes a short-term load forecasting method based on a multi-branch CNN architecture and Bayesian optimisation. By using different sizes of convolutional kernels in different branches, different time-scale features of power load data are captured to improve the identification of rapid changes and potential long-term trends. In addition, the hyperparameters of the forecasting model are automatically adjusted by a Bayesian optimisation algorithm to achieve the best forecasting performance. In forecasting experiments on real load data, the method in this paper significantly improves the forecasting accuracy compared to baseline models. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Convolutional neural networks

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Nonconvex Noise-Tolerant Neural Model for Repetitive Motion of Omnidirectional Mobile Manipulators

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1766-1768页

作者： Zhongbo Sun Shijun Tang Jiliang Zhang Junzhi Yu the Department of Control Engineering Changchun University of TechnologyChangchun 130012China IEEE College of Information Science and Engineering Northeastern UniversityShenyang 110819China the State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and RoboticsCollege of EngineeringPeking UniversityBeijing 100871China

Dear Editor,Quadratic programming problems(QPs)receive a lot of attention in various fields of science computing and engineering applications,such as manipulator control[1].Recursive neural network(RNN)is considered t... 详细信息

关键词： directional programming hardware

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3D Object Pose Estimation Based on End-to-End Differentiable Perspective Projection 43

3D Object Pose Estimation Based on End-to-End Differentiable...

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43rd Chinese control Conference, CCC 2024

作者： Cai, Yuheng Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Locating 3D objects from a single RGB image via perspective projection is a long-standing problem in computer vision. Inspired by differentiable geometry methods in the field of camera relocation, we apply this neural network combined with differentiable perspective projection to form an end-to-end architecture to the field of object position estimation through object 3D reconstruction methods. The proposed method uses a differentiable LM algorithm for end-to-end pose estimation to achieve higher accuracy, and the gradient is passed back to the neural network to guide its learning. At the same time, we propose a virtual view generation algorithm for augmenting the data to improve the algorithm's sensitivity to the size of the co-vision region. Through experiments, we prove the effectiveness of our method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Neural networks

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Improving Collision-Free Success Rate For Object Goal Visual Navigation Via Two-Stage Training With Collision Prediction

arXiv

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arXiv 2025年

作者： Lian, Shiwei Zhang, Feitian Robotics and Control Laboratory Department of Advanced Manufacturing and Robotics College of Engineering State Key Laboratory of Turbulence and Complex Systems Peking University Beijing100871 China

The object goal visual navigation is the task of navigating to a specific target object using egocentric visual observations. Recent end-to-end navigation models based on deep reinforcement learning have achieved remarkable performance in finding and reaching target objects. However, the collision problem of these models during navigation remains unresolved, since the collision is typically neglected when evaluating the success. Although incorporating a negative reward for collision during training appears straightforward, it results in a more conservative policy, thereby limiting the agent’s ability to reach targets. In addition, many of these models utilize only RGB observations, further increasing the difficulty of collision avoidance without depth information. To address these limitations, a new concept—collision-free success is introduced to evaluate the ability of navigation models to find a collision-free path towards the target object. A two-stage training method with collision prediction is proposed to improve the collision-free success rate of the existing navigation models using RGB observations. In the first training stage, the collision prediction module supervises the agent’s collision states during exploration to learn to predict the possible collision. In the second stage, leveraging the trained collision prediction, the agent learns to navigate to the target without collision. The experimental results in the AI2-THOR environment demonstrate that the proposed method greatly improves the collision-free success rate of different navigation models and outperforms other comparable collision-avoidance methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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A Battery control Strategy for Sequential Utilization of Energy Storage systems in Power Batteries 7

A Battery Control Strategy for Sequential Utilization of Ene...

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7th IEEE advanced Information Technology, Electronic and Automation control Conference, IAEAC 2024

作者： Li, Bowen Cui, Shijie Zhu, Lizhong Shenyang Ligong University College of Automation and Electrical Engineering Liaoning China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9798350339161

With the widespread adoption of energy storage systems utilizing power batteries, battery lifespan degradation has become a primary constraint on system performance. To address this issue, this study proposes a lifespan-optimized battery control strategy. Firstly, a battery lifespan calculation model for the energy storage system is established, taking into detailed consideration key parameters such as battery State of Charge (SOC). Secondly, a control strategy based on SOC for charging and discharging is designed, aiming to minimize battery lifespan consumption to the greatest extent possible. Finally, experimental results demonstrate that the proposed control strategy significantly improves the lifespan of the energy storage system compared to existing strategies. This research provides an effective means of control for the long-term stable operation of power battery systems. © 2024 IEEE.

关键词： Charging (batteries)

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Industrial Internet for intelligent manufacturing:past, present, and future

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Frontiers of Information Technology & Electronic Engineering 2024年第9期25卷 1173-1192页

作者： Chi XU Haibin YU Xi JIN Changqing XIA Dong LI Peng ZENG State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Key Laboratory of Networked Control Systems Chinese Academy of SciencesShenyang 110016China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Beijing 100049China

Industrial Internet, motivated by the deep integration of new-generation information and communication technology(ICT) and advanced manufacturing technology, will open up the production chain, value chain, and industry chain by establishing complete interconnections between humans, machines, and things. This will also help establish novel manufacturing and service modes, where personalized and customized production for differentiated services is a typical paradigm of future intelligent manufacturing. Thus, there is an urgent requirement to break through the existing chimney-like service mode provided by the hierarchical heterogeneous network architecture and establish a transparent channel for manufacturing and services using a flat network architecture. Starting from the basic concepts of process manufacturing and discrete manufacturing, we first analyze the basic requirements of typical manufacturing tasks. Then, with an overview on the developing process of industrial Internet, we systematically compare the current networking technologies and further analyze the problems of the present industrial *** this basis, we propose to establish a novel “thin waist” that integrates sensing, communication, computing, and control for the future industrial Internet. Furthermore, we perform a deep analysis and engage in a discussion on the key challenges and future research issues regarding the multi-dimensional collaborative sensing of task–resource, the end-to-end deterministic communication of heterogeneous networks, and virtual computing and operation control of industrial Internet.

关键词： intelligent manufacturing Industrial Internet Thin waist Transparent service Manufacturing as a service

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