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arXiv 2023年

作者： Liu, Wenjie Li, Yifei Sun, Jian Wang, Gang Chen, Jie National Key Lab of Autonomous Intelligent Unmanned Systems School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chonqing401120 China Department of Control Science and Engineering Tongji University Shanghai201804 China

This paper investigates the problem of data-driven stabilization for linear discrete-time switched systems with unknown switching dynamics. In the absence of noise, a data-based state feedback stabilizing controller can be obtained by solving a semi-definite program (SDP) on-the-fly, which automatically adapts to the changes of switching dynamics. However, when noise is present, the persistency of excitation condition based on the closed-loop data may be undermined, rendering the SDP infeasible. To address this issue, an auxiliary function-based switching control law is proposed, which only requires intermittent SDP solutions when its feasibility is guaranteed. By analyzing the relationship between the controller and the system switching times, it is shown that the proposed controller guarantees input-to-state practical stability (ISpS) of the closed-loop switched linear system, provided that the noise is bounded and the dynamics switches slowly enough. Two numerical examples are presented to verify the effectiveness of the proposed controller. © 2023, CC BY.

关键词： controllers

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Research Status of 6LoWPAN in the Field of Internet of Things 5

Research Status of 6LoWPAN in the Field of Internet of Thing...

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5th International Conference on Automation, control and Robotics engineering, CACRE 2020

作者： Zhao, Liang Wang, Guangwen School of Control Science and Engineering Dalian University of Technology Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian China Dalian University of Technology School of Control Science and Engineering Dalian China

ISBN: (纸本)9781728198880

The increasing number of wireless sensor nodes brings more application markets and challenges to the Internet of things (IoT). The traditional IPv4 address resources cannot meet the needs of the development of the IoT, so we need a communication mechanism with better compatibility and scalab.lity. With the proposal of the 6LoWPAN protocol, the application of 6LoWPAN to the communication network of the IoT has become the focus of research. This paper studies the research status of 6LoWPAN in the field of Internet of things in the past four years, and analyzes the system architecture, system composition and monitoring parameters of 6LoWPAN through different application scenarios. Experiments in related literatures show that 6LoWPAN has stable network transmission performance and can be used for precise monitoring and management in combination with web applications. In addition, RPL routing protocol security algorithm can be one of the future research directions. © 2020 IEEE.

关键词： Internet of things

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Short-term wind power forecast with turning weather based on DBSCAN-RFE-LightGBM

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Renewable Energy 2025年 251卷

作者： Wu, Zhenlong Fan, Xinyu Bian, Guibin Liu, Yanhong Zhang, Xiaoke Chen, YangQuan School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Zhengzhou University Luoyang471000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Electric Power Research Institute of State Grid Henan Electric Power Company Zhengzhou450052 China Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

At present, the wind power prediction technology is becoming more and more mature, however, the turning weather brings a decrease in prediction accuracy due to its suddenness and instability. In this paper, a wind power prediction method considering the turning period and non-turning period respectively is proposed to weaken the adverse effects caused by turning weather. Firstly, the prediction effects of multiple models are compared, density-based spatial clustering of applications with noise (DBSCAN) is selected as the outlier processing method, recursive feature elimination (RFE) is used as the feature selection method, and Light gradient boosting machine (LightGBM) is used for prediction. The combined prediction method based on DBSCAN-RFE-LightGBM can reduce the influence of abnormal data and redundant features and improve the prediction effect. Then, the sliding window is set to detect the turning period. Considering that the turning weather is an emergency and does not happen frequently, the amount of data is small, which leads to the inability to train the model well. Generative adversarial networks (GAN) are applied to expand the turning period data. The LightGBM is trained and predicted by using the expended turning period data. Finally, the time-division prediction results are merged. Using the data collected from wind farms for short-term power prediction experiments, the time-segment prediction method proposed in this paper with GAN reduces MAE by 1.913 and RMSE by 3.351 on a single unit compared with the non-differentiated period. © 2025 Elsevier Ltd

关键词： Merging

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Algorithms for intelligent control of Multi-Link Walking Robots with Self-Learning Capabilities 22

Algorithms for Intelligent Control of Multi-Link Walking Rob...

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22nd International Conference on Digital Signal Processing and its Applications, DSPA 2020

作者： Danilov, Vladimir Diane, Sekou Gonchareko, Vladimir Artamonov, Alexander Moscow Aviation Institute National Research University Dept. of Systems of Automatic and Intelligent Control Moscow Russia Lab. of System Integration of Control Technologies Institute of Control Problems Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9781728175287

The main types of structures of walking robots are considered and the choice of the design of the implemented layout of a six-legged insectomorphic robot is justified. Based on the results of the analysis of known approaches to the design of walking systems and the selected type of robot, solutions of forward and reverse kinematics problems for its joints are described. Kinematic and dynamic models of a six-legged walking robot are calculated and implemented programmatically. A computer simulation model of a six-legged walking robot is constructed that combines a 3d representation of the robot and the dynamics of its movement. The procedure for adjusting the control algorithms for a multilink structure is suggested to adapt for the uncertainties in the robot construction and the surrounding environment. Verification of the proposed mathematical models was carried out on virtual and hardware samples of walking robots. © 2020 IEEE.

关键词： Kinematics

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Cooperative target capture using predefined-time consensus over fixed and switching networks

arXiv

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arXiv 2021年

作者： Sinha, Abhinav Kumar, Shashi Ranjan The Intelligent Systems & Control Lab Department of Aerospace Engineering Indian Institute of Technology Powai Bombay Mumbai400076 India

We propose predefined-time consensus-based cooperative guidance laws for a swarm of interceptors to simultaneously capture a target capable of executing various kinds of motions. Unlike leader-follower cooperative guidance techniques, the swarm of interceptors has no leader and each interceptor executes its own guidance command in a distributive fashion, thus obviating the residency of the mission over a single interceptor. We first design cooperative guidance commands subject to target's mobility, followed by the same when the target is stationary, and also account for interceptors' changing topologies. We further show through rigorous analysis that the proposed cooperative guidance laws guarantee consensus in the interceptors' time-to-go values within a predefined-time. The proposed design allows a feasible time of consensus in time-to-go to be set arbitrarily at will during the design regardless of the interceptors' initial time-to-go values, thereby ensuring a simultaneous target interception. We also demonstrate the efficacy of the proposed design via simulations for interceptors connected over static and dynamic networks. © 2021, CC BY-NC-SA.

关键词： Switching networks

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Distributed best response dynamics for Nash equilibrium seeking in potential games

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control Theory and Technology 2020年第3期18卷 324-332页

作者： Shijie HUANG Peng YI Key Lab of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100190China Department of Control Science&Engineering Tongji UniversityShanghai 201804China Shanghai Institute of Intelligent Science and Technology Tongji UniversityShanghai 201804China

In this paper,we consider distributed Nash equilibrium(NE)seeking in potential games over a multi-agent network,where each agent can not observe the actions of all its *** on the best response dynamics,we design a distributed NE seeking algorithm by incorporating the non-smooth finite-time average tracking dynamics,where each agent only needs to know its own action and exchange information with its neighbours through a communication *** give a sufficient condition for the Lipschitz continuity of the best response mapping for potential games,and then prove the convergence of the proposed algorithm based on the Lyapunov *** simulations are given to verify the resultandillustrate the effectiveness of the algorithm.

关键词： Distributed algorithms Nash equilibrium seeking best response dynamics non-smooth finite-time tracking dynamics potential games

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Competition and Cooperation Mechanism Between Agency Selling and Wholesale: An Application of the Emerging E-commerce Model

Competition and Cooperation Mechanism Between Agency Selling...

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IEEE International Conference on Industrial engineering and engineering Management

作者： Haonan Wang C. K. M. Lee Ping Ji Gang Li Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong China Laboratory for Artificial Intelligence in Design Hong Kong Science Park New Territories Hong Kong SAR China School of Intelligent Finance and Business XJTLU Entrepreneur College (Taicang) Xi'an Jiaotong - Liverpool University China School of Management Xi'an Jiaotong University The State Key Lab for Manufacturing Systems Engineering The Key Lab of the Ministry of Education for Process Control and Efficiency Engineering Xi'an China

Recently, the platform economy allows enterprises to collab.rate with business partners and provide additional channels for various parties. E-commerce platforms have become integral channels for connecting suppliers with consumers. In the platform economy, agency selling and reselling are two predominant sales models that often coexist for the same product types, resulting in a competitive relationship. This study analyzes transaction data for 30,000 Stock Keeping Units (SKUs) provided by the Chinese e-commerce platforms over one month. We employ three models to compare the sales quantity and profits of manufacturers and online platforms and to identify the most efficient mode for stakeholders based on the model establishment and empirical evidence. Our findings suggest that apart from the existing channel to provide products to customers, manufacturers enter the platform which will increase the profit of platform operators. On the other hand, platform operators may also affect the profit of the manufacturers.

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Sparse Prior Is Not All You Need: When Differential Directionality Meets Saliency Coherence for Infrared Small Target Detection

arXiv

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arXiv 2024年

作者： Zhou, Fei Fu, Maixia Qian, Yulei Yang, Jian Dai, Yimian Ministry of Education Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou China Nanjing Marine Radar Institute Nanjing China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China

Infrared small target detection is crucial for the efficacy of infrared search and tracking systems. Current tensor decomposition methods emphasize representing small targets with sparsity but struggle to separate targets from complex backgrounds due to insufficient use of intrinsic directional information and reduced target visibility during decomposition. To address these challenges, this study introduces a Sparse Differential Directionality prior (SDD) framework. SDD leverages the distinct directional characteristics of targets to differentiate them from the background, applying mixed sparse constraints on the differential directional images and continuity difference matrix of the temporal component, both derived from Tucker decomposition. We further enhance target detectability with a saliency coherence strategy that intensifies target contrast against the background during hierarchical decomposition. A Proximal Alternating Minimization-based (PAM) algorithm efficiently solves our proposed model. Experimental results on several real-world datasets validate our method’s effectiveness, outperforming ten state-of-the-art methods in target detection and clutter suppression. Our code is availab.e at https://***/GrokCV/SDD. Copyright © 2024, The Authors. All rights reserved.

关键词： Tensors

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Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification

SSRN

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SSRN 2023年

作者： Wang, Jiabao Li, Yang Wei, Xiu-Shen Li, Hang Miao, Zhuang Zhang, Rui Army Engineering University of PLA Jiangsu Nanjing210007 China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Jiangsu Key Lab of Image and Video Understanding for Social Security School of Computer Science and Engineering Nanjing University of Science and Technology Jiangsu Nanjing210094 China State Key Lab. for Novel Software Technology Nanjing University Jiangsu Nanjing210023 China

Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID). However, it is found that the unsupervised learning of fine-grained visual classification (FGVC) is more challenging than GOC and person re-ID. In order to bridge the gap between unsupervised and supervised learning for FGVC, we investigate the essential factors for the performance gap. Furthermore, we propose a simple, effective, and practical method, termed as UFCL, to alleviate the gap. Three key issues are concerned and improved: First, we introduce a robust and powerful backbone, ResNet50-IBN, which has an ability of domain adaptation when we transfer ImageNet pre-trained models to FGVC tasks. Next, we propose to introduce HDBSCAN instead of DBSCAN to do clustering, which can generate better clusters for adjacent categories with fewer hyper-parameters. Finally, we propose a weighted feature agent and its updating mechanism to do contrastive learning, which can improve the optimization process of learning the parameters of the network. The effectiveness of our UFCL is verified on four public FGVC datasets. Under the unsupervised FGVC setting, we achieve state-of-the-art results, and analyze the key factors and the important parameters to provide a practical guidance. © 2023, The Authors. All rights reserved.

关键词： Image classification

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Real-time battery SOC estimation under hybrid power conditions using fast-OCV curve with unscented Kalman filters

Real-time battery SOC estimation under hybrid power conditio...

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IEEE Metrology for Aerospace

作者： Zhuoyao He David Martín Gómez Arturo de la Escalera Hueso Xingcai Lu José María Armingol Moreno Pablo Flores Peña Key Lab. for Power machinery and Engineering of M. O. E. Shanghai Jiao Tong University Shanghai P R China Intelligent Systems Lab (LSI) Universidad Carlos III de Madrid Leganés Madrid Drone Hopper S.L. Leganés Madrid

Unmanned aerial vehicles (UAVs) are drawing more and more attentions recent years and widely applied. Nevertheless, it is generally challenged by short time of duration because of the lack of energy density for battery. A robust power supply is indispensable for advanced UAVs thus hybrid-power might be a promising solution. State of charge (SOC) estimation is essential for power system of UAVs. While, accurate SOC estimation always challenged partly ascribed to accurate open circuit voltage identification. Considering the actual working condition of battery under hybrid condition, this paper proposed a novel method “fast-OCV” for obtaining open circuit voltage of battery. It is proved that fast-OCV showed great advantages related to simplicity and time cost over traditional way for obtaining OCV. Moreover, fast-OCV also showed better accuracy over traditional OCV. As a supplementary, this paper also proved that limited memory recursive least square algorithm was a good way for parameter estimation. With such algorithm, distinct noise was encountered when using single-mode. In compare, batch mode for parameter estimation showed much better performance with distinctively weaker noise.

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