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Chinese Control and Decision Conference, CCDC

作者： Decai Zhang Huaiyu Wu Mian Hu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

To effectively enhance the utilization of renewable energy in multi-microgrid systems while ensuring fair distribution of benefits among microgrids, this paper proposes a multi-microgrid multi-energy optimal scheduling strategy based on hybrid energy storage system (HESS) and sharing technology. Firstly, a novel multi-microgrid multi-energy shared energy storage system framework is designed, considering that a HESS is equipped with hydrogen storage system, electric boiler, heat storage tank, P2G devices and gas storage tank as well as coordinates the multi-energy sharing among microgrids. All microgrids and HESS are composed into a microgrid alliance for cooperative game. Secondly, the alternating direction method of multipliers (ADMM) is used to solve the optimal energy transaction volume and transaction price between each microgrid and HESS. Then, the asymmetric Nash negotiation (ANN) method is used to fairly distribute the benefits obtained by each subject. Finally, the simulation experiment shows that the proposed multi-microgrid multi-energy optimal scheduling strategy can not only meet the needs of various energy sources of microgrid, but also improve the utilization rate of renewable energy and the economic benefits of each subject.

关键词： Renewable energy sources Privacy Costs Simulation Microgrids Optimal scheduling Minimization

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Distributed operational management of microgrids: a second order dual update approach

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IFAC-PapersOnLine 2023年第2期56卷 1540-1545页

作者： Giulio Ferro Michela Robba Federico Delfino Rabab Haider Anuradha M. Annaswamy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Genoa Italy Department of Mechanical Engineering Massachusetts Institute of Technology Cambridge MA 02141 USA Department of of Electrical Electronic Telecommunications Engineering and Naval Architecture University of Genova

This paper develops a Distributed Energy Management System (EMS) to optimally allocate electric and thermal power production in a polygenerative microgrid. The EMS problem is formulated as a multiperiod convex optimization problem and solved using AL-SODU, a new distributed algorithm based on the augmented Lagrangian method with second order dual updates. The proposed AL-SODU algorithm significantly outperforms state of the art algorithms employing first order dual updates, with 15-times speedup in convergence speed. A case study of the EMS based on AL-SODU is conducted on the Smart Polygeneration Microgrid (SPM) located on the Savona Campus of University of Genova (Italy). The EMS determines the optimal schedules for electric and thermal power plants every 15-minutes. This real time scheduling of the microgrid is enabled by the Al-SODU algorithm, which solves the scheduling problem in 1.86s.

关键词： Microgrids distributed control second order methods

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Signal Processing for Acoustic Emission Signature Analysis and Defect Detection

Signal Processing for Acoustic Emission Signature Analysis a...

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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Yeldos A. Altay Dmitry O. Kuzivanov Dinara A. Altay Alexey V. Fedorov Department of Robotics and Technical Means of Automation Satbayev University Almaty Kazakhstan Faculty of Control Systems and Robotics ITMO University Saint-Petersburg Russian Federation Department of Natural Sciences Military Engineering Institute of Radio Electronics and Communications Almaty Kazakhstan

This article presents the results of implementing a digital signal processing method for analyzing the acoustic emission (AE) signature and detecting defects such as cracks and pores. The signal processing method is based on a cascade connection of digital high-pass filters and ensures the selection of informative signals and increases the signal-to-interference ratio. In order to control the formation of defects in the process of selective laser melting, the paper presents the results of experimental testing of the cascade filtration method for detecting defects in the internal structure such as cracks and pores. The signal components recorded during the development of defects during the growth of additive manufacturing products were extracted. AE signatures were analyzed and statistical relationships were assessed. The relationship between the parameters of the AE signal and the values of laser radiation power has been identified, which characterizes the process of defect formation.

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A 5G-Based Switching Method between a Local Controller and an Edge Controller 6

A 5G-Based Switching Method between a Local Controller and a...

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6th International Conference on Intelligent robotics and Control engineering, IRCE 2023

作者： Wang, Xiulian Lin, Jinggao Jin, Xi Xia, Changqing Xu, Chi College of Automation and Electrical Engineering Shenyang Ligong University China Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9798350326338

With the rapid development of edge computing, industrial automation has evolved a two-layer distributed computing architecture, including local controllers communicating through wired networks and edge controllers communicating wirelessly. The edge controllers in existing studies use WIFI, which has a limited working distance and requires independent network deployment, so they are unsuitable for future large-scale complex industrial production. At present, 5G technology is undergoing rapid development in the field of industrial automation, with wide coverage and excellent mobility, gradually becoming suitable for future large-scale and complex industrial production scenarios. Therefore, this paper proposed an SW5G method based on 5G, which combined the local controller with the edge controller. The controllers were switched according to the constantly changing 5G network transmission delay, thereby optimizing the overall system control performance. Finally, simulation experiments demonstrated good control performance of SW5G in various network scenarios. © 2023 IEEE.

关键词： Controllers

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Stackelberg Game-Based Optimal Scheduling Strategy for Multi-Microgrid systems with Electricity-Heat Shared Energy Storage

Stackelberg Game-Based Optimal Scheduling Strategy for Multi...

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Chinese Automation Congress (CAC)

作者： Chao Peng Decai Zhang Mian Hu Huaiyu Wu Yang Chen Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Wuhan University of Science and Technology Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

To address the challenges of the complexity of electricity-heat coupling, the pollution of carbon emissions, the security of privacy information, and the uncertainty of renewable energy generations (REGs), this paper proposes a novel multi-microgrid electricity-heat shared energy storage system framework, considering that the integrated energy storage operator (IESO) is equipped with electric boiler and two types of energy storage (i.e., electrical energy storage and heat energy storage) devices, and each microgrid (MG) is equipped with combined heat and power system that coupled carbon capture system and power-to-gas device. Latin hypercube sampling is used to deal with the uncertainty of REGs. A distributed bi-level iterative algorithm based on Stackelberg game theory is designed, which effectively protects the users' privacy information, and finally a Stackelberg equilibrium strategy is obtained, where the IESO and each MG minimize its operating cost. Simulation results show that the proposed optimal scheduling strategy can effectively reduce the operating cost and carbon emissions of each MG, and increase the benefits of the IESO.

关键词： Privacy Uncertainty Costs Cogeneration Optimal scheduling Microgrids Thermal pollution Iterative methods Energy storage Resistance heating

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Estimation of Wrist Chattering Angle Based on Disturbance Observer 16

Estimation of Wrist Chattering Angle Based on Disturbance Ob...

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16th International Congress on Image and Signal Processing, BioMedical engineering and Informatics, CISP-BMEI 2023

作者： Zhang, Xinyu Sun, Zhenyu Shu, Bairui Yokoi, Hiroshi Yong, Xu Li, Guanglin Jing, Xiaobei The Siat Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518055 China The University of Electro-Communications Joint Doctoral Program for Sustainability Research Tokyo182-8585 Japan The University of Electro-Communications Department of Mechanical Engineering and Intelligent Systems Tokyo182-8585 Japan

ISBN: (纸本)9798350330755

Due to the physiological constraints and daily habits of hand movements, the wrist chattering effect (WCE) will inadvertently cause disturbance to the accuracy of fingers' pattern recognition, when healthy subjects or amputees undergoing mirror training control their fingers according to instructions. This paper proposes a method for estimating WCE angles using a disturbance observer. Based on the Denavit-Hartenberg (D-H) convention and inverse kinematics, the intervals of the WCE during finger flexion and extension are determined. The research objective is to eliminate disturbance terms containing redundant information referring to sliding mode anti-jittering methods, making subsequent machine learning models less susceptible to disturbances. © 2023 IEEE.

关键词： Inverse kinematics

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Gas Source Localization for UAV Using Infotaxis-Based Three-Dimensional Algorithm and Particle Filtering

Gas Source Localization for UAV Using Infotaxis-Based Three-...

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第43届中国控制会议

作者： Duan He Cheng Lei Wang Rong Zhang Yu Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Unmanned aerial vehicles(UAVs) are extensively utilized in gas source localization tasks due to their payload capacity and maneuverability. This paper presents a UAV gas source localization algorithm that utilizes three-dimensional Infotaxis and particle filter. The algorithm is designed for gas source localization of UAVs in dynamic outdoor airflow *** source localization process comprises UAV search area partitioning, particle filter initialization, observation and update of probability map, entropy calculation and direction selection, particle direction and weight update, and UAV movement. To validate the effectiveness of the algorithm, we build a CFD gas environment and UAV source localization platform, and compare it with traditional Infotaxis-based source localization algorithms. The proposed algorithm based on three-dimensional Infotaxis and particle filter demonstrates higher accuracy.

关键词： infotaxis particle filtering gas source localization olfactory drone path planning

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Truncated Cauchy Loss for Outlier-Robust Blind Image Deblurring

Truncated Cauchy Loss for Outlier-Robust Blind Image Deblurr...

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Chinese Control and Decision Conference, CCDC

作者： Xiaopan Li Shiqian Wu Qi Wu Institute of Robotics and Intelligent Systems School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China School of Software & Internet of Things Engineering Jiangxi University of Finance & Economics Nanchang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In complex imaging environments, captured images often contain outliers like impulse noise, Cauchy noise, and saturated pixels, posing significant challenges for image deblurring. While existing blind deblurring methods can address outliers to a certain extent, the incorporation of intricate operations tends to amplify the complexity of the deblurring process. In light of these challenges, we present a simple yet robust blind deblurring algorithm for handling images with outliers. To alleviate the effect of outliers on kernel estimation, we introduce a truncated Cauchy loss function, which effectively suppresses outliers by truncating significant errors. Furthermore, we employ a statistics-based approach for outlier detection, eliminating the need for heuristic methods. The proposed approach is shown to be easily implementable and extendable for non-blind deblurring. Experimental results demonstrate that the proposed algorithm outperforms state-of-the-art methods for both blurred images with outliers and those without.

关键词： Noise Imaging Estimation Linear programming Data models Image restoration Complexity theory

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A Novel Gas Classification Method Based on The Improved GasNet

A Novel Gas Classification Method Based on The Improved GasN...

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第43届中国控制会议

作者： Xiaolin Qin Lei Cheng Xiang Tao Engineering Research Center for Metallurgical Automation and Measurement Technology of Ministry of Education Institute of Robotics and Intelligent Systems Wuhan University of Science and Technology School of Information Science and Engineering Wuhan University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Accurately and promptly identifying harmful gases in the environment can effectively prevent many accidents. Most existing pattern recognition methods are focused on addressing gas classification problems in static scenarios, but the real world is a dynamic and changing environment. Therefore, researching gas classification in continuous learning scenarios will better meet the needs of suddenly emerging gas classification tasks in real-world environments. To address this issue, an incremental learning model was introduced into gas classification, and an improved deep convolutional network was proposed for gas image feature extraction. The proposed model and other baseline methods experimented on an open-source gas dataset. The proposed model reduces knowledge loss due to catastrophic forgetting and effectively classifies the 10 gas samples in the dataset in continuous learning scenarios compared to non-incremental methods. It outperforms other baseline incremental methods by optimizing the network's shortcut connections, making the feature extraction network easier to train and improving gas classification performance. In dynamic learning scenarios, the proposed model achieved a classification accuracy of 86.30% for 10 gas *** experimental results demonstrate that the proposed method effectively mitigates catastrophic forgetting interference and completes gas classification tasks in continuous learning scenarios.

关键词： Gas classification Incremental learning Shortcut connection Catastrophic forgetting

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Algorithm for Robustness Estimation of Large Deviations in Linear Discrete-Time systems 17th

Algorithm for Robustness Estimation of Large Deviations in...

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17th International Conference on Informatics in Control, Automation and robotics, ICINCO 2020

作者： Vunder, Nina Dudarenko, Natalia Institute of Control Engineering TU Braunschweig Hans-Sommer-Str. 66 Braunschweig Germany Department of Control Systems and Industrial Robotics ITMO University 49 Kronverksky Pr. Saint-Petersburg Russia

ISBN: (纸本)9783030924416

The paper presents the algorithm for robustness estimation of large deviations in free motion of linear discrete-time systems. A tracking discrete-time systems with the modal control law are discussed, where the modal control law is designed taking into account the value of delay and the deviation. Two cases of discrete-time systems with control signal delay are considered in the paper. The first case relates to predictable delay of control signal, and the second one relates to unpredictable delay of control signal. It is assumed that parameters of the system are linearly dependent on the uncertainties. The problem is solved with the state space approach and the sensitivity theory methods. An upper bound estimation of trajectory deviations for discrete-time systems is obtained. The estimation contains the condition number of the eigenvectors matrix of the system state matrix. Therefore, sensitivity functions of singular values of the eigenvectors matrix are used to calculate the robustness estimation of the deviations. Based on the obtained equations, an algorithm for the robustness estimation of large deviations in linear discrete-time systems with parametric uncertainties is proposed. The proposed method is compared with an alternative LMI based approach for the peak estimation problem. Advantages and disadvantages of both approaches are illustrated with examples. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Sensitivity analysis

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