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42nd Chinese control Conference, CCC 2023

作者： Liu, Zhi Zhang, Lin Wang, Shoukun Niu, Tianwei Xu, Yongkang Cao, Jin School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China School of Automation Beijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information Technology Beijing100081 China

ISBN: (纸本)9789887581543

Path planning is one of the most critical links in mobile robots. Its timeliness, security and accessibility are crucial to the development and wide application of mobile robots. However, in solving the problem of path planning, the most popular A∗ algorithm has some problems, such as heuristic function cannot be estimated accurately, node redundancy, path is not smooth, and obstacle avoidance cannot be achieved in real time. To solve these problems, A fusion algorithm of improved A∗ combined with reverse path and dynamic window method (DWA-IMP-A∗) was proposed. The algorithm refines the heuristic function by incorporating the reverse path. The node optimization algorithm is used to further reduce the path length. The generated trajectories are smoothed by cubic spline interpolation. At the same time, it is integrated with the improved DWA algorithm to improve the efficiency and safety of robot path planning. The algorithm takes ROS mobile robot as the carrier and is tested under typical road conditions. Compared with A∗ algorithm, the planning time is reduced by 54.6% and the path length is reduced by 6.37%. Experimental results verify the effectiveness and robustness of the algorithm. The research results have certain reference significance for the path planning of various types of mobile robots and the research of driverless vehicles. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Motion planning

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Reduction of data amount in data-driven design of linear quadratic regulators

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control Theory and Technology 2024年第4期22卷 532-542页

作者： Shinsaku Izumi Xin Xin School of Systems Engineering Kochi University of TechnologyKamiKochi782-8502Japan School of Automation Southeast Universityand Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of EducationNanjing210096JiangsuChina

This paper discusses the data-driven design of linear quadratic regulators,i.e.,to obtain the regulators directly from experimental data without using the models of *** particular,we aim to improve an existing design method by reducing the amount of the required experimental *** the data amount leads to the cost reduction of experiments and computation for the data-driven *** present a simplified version of the existing method,where parameters yielding the gain of the regulator are estimated from only part of the data required in the existing *** then show that the data amount required in the presented method is less than half of that in the existing method under certain *** addition,assuming the presence of measurement noise,we analyze the relations between the expectations and variances of the estimated parameters and the *** a result,it is shown that using a larger amount of the experimental data might mitigate the effects of the noise on the estimated *** results are verified by numerical examples.

关键词： Data-driven design Linear quadratic regulators Linear systems Riccati equation Stochastic properties

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Learning Scalable Task Assignment with Imperative-Priori Conflict Resolution in Multi-UAV Adversarial Swarm Defense Problem

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Journal of Systems Science & Complexity 2024年第1期37卷 369-388页

作者： ZHAO Zhixin CHEN Jie XIN Bin LI Li JIAO Keming ZHENG Yifan School of Electronics and Information Engineering Tongji UniversityShanghai 201804China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China School of Automation Beijing Institute of TechnologyBeijing 100081China National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing 100081China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China.

The multi-UAV adversary swarm defense(MUASD)problem is to defend a static base against an adversary UAV swarm by a defensive UAV *** the problem into task assignment and low-level interception strategies is a widely used ***-based approaches for task assignment are a promising *** studies on learning-based methods generally assume decentralized decision-making architecture,which is not beneficial for conflict *** contrast,centralized decision-making architecture is beneficial for conflict resolution while it is often detrimental to *** achieve scalability and conflict resolution simultaneously,inspired by a self-attention-based task assignment method for sensor target coverage problem,a scalable centralized assignment method based on self-attention mechanism together with a defender-attacker pairwise observation preprocessing(DAP-SelfAtt)is ***,an imperative-priori conflict resolution(IPCR)mechanism is proposed to achieve conflict-free ***,the IPCR mechanism is parallelized to enable efficient *** validate the algorithm,a variant of proximal policy optimization algorithm(PPO)is employed for training in scenarios of various *** experimental results show that the proposed algorithm not only achieves conflict-free task assignment but also maintains scalability,and significantly improve the success rate of defense.

关键词： Conflict resolution reinforcement learning scalability task assignment.

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RIS-assisted Channel Prediction Model for Mine V2X Systems 5

RIS-assisted Channel Prediction Model for Mine V2X Systems

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5th International Conference on Computer, Big Data and Artificial Intelligence, ICCBD+AI 2024

作者： Cheng, Yuanxun Hu, Qingsong Luo, Yujia Zhang, Yuansheng China University of Mining and Technology School of Information and Control Engineering Xuzhou China Beijing Key Laboratory of Process Automation in Mining & Metallurgy State Key Laboratory of Intelligent Optimized Manufacturing in Mining & Metallurgy Process Beijing China

ISBN: (纸本)9798331533991

The complex and dynamic environment of mines leads to time-variability and uncertainty in channel propagation, which affects the stability and reliability of Vehicle-to-Everything (V2X)communication in mine networks. Channel prediction can help mitigate these issues. Introducing reconfigurable intelligence surface (RIS) into the mine V2X system can enhance signal coverage and quality in the complex mine environment. To address the issue of long-term error accumulation in existing channel prediction models, this paper analyzes the prediction error of channel state information (CSI) in mine V2X systems. It was observed that the error distribution exhibits characteristics of an approximate normal distribution, revealing its predictability. Utilizing this characteristic, this paper proposes an error correction strategy to suppress long-term error accumulation during the prediction process. Furthermore, an adaptive method for optimizing RIS phases is designed based on the Snow Ablation Optimizer. Specifically, this paper utilizes a metaheuristic optimization algorithm and deep learning techniques to propose a mine V2X channel prediction model that incorporates the error correction strategy. Experimental results show that optimizing the RIS phase can effectively enhance channel gain, and the mine V2X channel prediction model incorporating the error correction strategy can effectively suppress cumulative errors during the prediction process, thereby improving prediction accuracy. © 2024 IEEE.

关键词： Normal distribution

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Optimized Hybrid control for Attitude Adjustment of Downhole Directional Drilling Tools 50

Optimized Hybrid Control for Attitude Adjustment of Downhole...

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

作者： Xiao, Jing Wang, She Cai, Zhen School of Information Engineering Wuhan City Polytechnic University Wuhan430064 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781665464543

This study delves into the critical role of attitude control in downhole directional drilling tools, focusing on the complex coupling between inclination and azimuth in the motion model, particularly the time-varying nature of azimuth adjustments. By implementing separate control strategies for inclination and azimuth, the research integrates a comprehensive hybrid control system. It rigorously examines the stability of the closed-loop systems and validates the effectiveness and applicability of the hybrid control method through extensive simulations. The system demonstrates significant robustness and adaptability, enhancing drilling precision and efficiency. © 2024 IEEE.

关键词： State feedback

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Event-triggered Adaptive control of Switched Nonlinear Cyber-physical Systems

Event-triggered Adaptive Control of Switched Nonlinear Cyber...

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2024 China automation Congress, CAC 2024

作者： Yuan, Manman Qian, Wei School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo454003 China Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment Jiaozuo454003 China

ISBN: (纸本)9798350368604

The event-triggered control problem of switched nonlinear cyber-physical systems (CPSs) is investigated under average dwell time (ADT). A new dynamic gain is proposed, which can effectively compensate for the unknown growth rate and measurement sensitivity. Then, a switched observer integrated with a novel dynamic gain is designed and an event-triggered output feedback controller is developed, which can effectively mitigate the communication burden. Finally, it is proved that all the closed-loop signals are bounded and all system states converge to the origin. Accordingly, the effectiveness of the presented scheme is verified through the simulation of switched RLC circuit system. © 2024 IEEE.

关键词： Adaptive control systems

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Electric Field Simulation and Optimization of a Conical Current Transformer 18th

Electric Field Simulation and Optimization of a Conical Curr...

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18th Annual Conference of China Electrotechnical Society, ACCES 2023

作者： Yin, Xuzhen Zeng, Jianbin Zeng, Jin Yang, Yang School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361024 China

ISBN: (纸本)9789819710676

Cast-resin type current transformers are widely used in power systems due to their good insulation, light weight and high reliability. Compared with the oil-immersed current transformer, the external electric field strength of the cast-resin current transformer is more complex and unevenly distributed. To improve this problem, this paper takes a kind of conical casting type current transformer as the object. Firstly, a geometrical model is established to simulate and analyze its external electric field distribution, then an improvement scheme is proposed, and finally the improvement scheme is optimized. The results of this study can provide a reference for the design of the transformer and the optimization of the local discharge. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Partial discharges

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Alarm Prediction with Variational Output Dimension for Alarm Floods Using Transformer 43

Alarm Prediction with Variational Output Dimension for Alarm...

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43rd Chinese control Conference, CCC 2024

作者： Pang, Long Jiang, Wenbin Hu, Wenkai Wang, Zhuang Cao, Weihua 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 Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

Industrial alarm systems play crucial roles in assessing the production status and ensuring process safety. However, the presence of alarm floods can make alarm systems partially or fully fail, and thus would cause serious consequences. Alarm prediction, as an advanced approach to address alarm floods, offers operators decision supports when an alarm flood occurs. Existing alarm prediction methods requires that the output alarm sequences are of a fixed dimension, making such methods unable to adapt to the changing alarm rate. Accordingly, this paper proposes an alarm prediction model based on Transformer. The proposed model can predict alarm sequences with variational dimensions and can also achieve remarkable accuracy. The effectiveness of the proposed method is demonstrated by a case study with data from the Vinyl Acetate Monomer (VAM) simulation model. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Polyvinyl acetates

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GRAMO:geometric resampling augmentation for monocular 3D object detection

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Frontiers of Computer Science 2024年第5期18卷 161-169页

作者： He GUAN Chunfeng SONG Zhaoxiang ZHANG School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and Computing State Key Laboratory of Multimodal Artificial Intelligence SystemsInstitute of Automation Chinese Academy of SciencesBeijing 100190China

Data augmentation is widely recognized as an effective means of bolstering model ***,when applied to monocular 3D object detection,non-geometric image augmentation neglects the critical link between the image and physical space,resulting in the semantic collapse of the extended *** address this issue,we propose two geometric-level data augmentation operators named Geometric-Copy-Paste(Geo-CP)and Geometric-Crop-Shrink(Geo-CS).Both operators introduce geometric consistency based on the principle of perspective projection,complementing the options available for data augmentation in monocular ***,Geo-CP replicates local patches by reordering object depths to mitigate perspective occlusion conflicts,and Geo-CS re-crops local patches for simultaneous scaling of distance and scale to unify appearance and *** operations ameliorate the problem of class imbalance in the monocular paradigm by increasing the quantity and distribution of geometrically consistent *** demonstrate that our geometric-level augmentation operators effectively improve robustness and performance in the KITTI and Waymo monocular 3D detection benchmarks.

关键词： 3D detection monocular augmentation geometry

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Pre-trained Language Model - Based Real-time Formation Lithology Identification Method for Drilling Process

Pre-trained Language Model - Based Real-time Formation Litho...

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2024 China automation Congress, CAC 2024

作者： Liu, Jianyang 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

Geological exploration is essential for economic and social progress, with lithology identification being a key technology that improves exploration precision and resource development efficiency. This paper presents a real-time identification method of formation lithology in drilling process based on pre-training language model, which is divided into three stages. In this first stage, the drilling data undergoes rigorous cleaning, feature selection, and normalization to eliminate noise and anomalies. In the second stage, key model inputs such as weight on bit (WOB), rate of penetration (ROP), rotation speed (RPM), torque, and pump volume (P) are identified through detailed drilling mechanism analysis. In the last stage, a real-time identification method of formation lithology in drilling process based on pre-training language model is proposed, which realizes high-precision real-time identification in drilling process. The effectiveness of the proposed method is proved by comparison with common methods. © 2024 IEEE.

关键词： Lithology

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