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arXiv 2024年

作者： Yuan, Meng Wang, Ye Manzie, Chris Xu, Zhezhuang Chai, Tianyou The Department of Electrical Engineering Chalmers University of Technology Gothenburg41296 Sweden The Department of Electrical and Electronic Engineering The University of Melbourne ParkvilleVIC3010 Australia The College of Electrical Engineering and Automation Fuzhou University Fuzhou350108 China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

Biaxial motion control systems are used extensively in manufacturing and printing industries. To improve throughput and reduce machine cost, lightweight materials are being proposed in structural components but may result in higher flexibility in the machine links. This flexibility is often position dependent and compromises precision of the end effector of the machine. To address the need for improved contouring accuracy in industrial machines with position-dependent structural flexibility, this paper introduces a novel contouring error-bounded control algorithm for biaxial switched linear systems. The proposed algorithm utilizes model predictive control to guarantee the satisfaction of state, input, and contouring error constraints for any admissible mode switching. In this paper, the switching signal remains unknown to the controller, although information about the minimum time the system is expected to stay in a specific mode is considered to be available. The proposed algorithm has the property of recursive feasibility and ensures the stability of the closed-loop system. The effectiveness of the proposed method is demonstrated by applying it to a high-fidelity simulation of a dual-drive industrial laser machine. The results show that the contouring error is successfully bounded within the given tolerance. © 2024, CC BY-NC-ND.

关键词： Closed loop systems

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A Comprehensive Methodology of Field-Oriented control Design With Parameter Variation Analysis for Interior Permanent Magnet Synchronous Machine Drives

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IEEE Access 2025年 13卷 89524-89541页

作者： Busarello, Tiago Davi Curi Bubshait, Abdullah Varaprasad, Oruganti V. S. R. Alsaleem, Abdulhakeem Simoes, Marcelo Godoy Federal University of Santa Catarina Department of Control Automation and Computation Engineering Florianopolis88040-900 Brazil King Faisal University College of Engineering Department of Electrical Engineering Al Ahsa31982 Saudi Arabia Group Department of Electrical Computer and Software Engineering OshawaONL1G 0C5 Canada Qassim University College of Engineering Department of Electrical Engineering Buraydah52571 Saudi Arabia University of Vaasa School of Technology and Innovations Vaasa65200 Finland

This paper proposes a comprehensive methodology for Field-Oriented control (FOC) with parameter variation analysis for Interior Permanent Magnet Synchronous Machines (IPMSM). The modeling approach for an IPMSM is first presented, followed by a step-by-step procedure for designing a vector-controlled strategy. The formulation is based on a dq-rotating reference frame aligned with the rotor shaft position. A key distinction of this methodology from traditional approaches is that the current controller is designed in the time domain based on desired time constants, while the speed control is formulated within a frequency response domain framework. The proposed hybrid approach enables accurate tuning of the Proportional-Integrator (PI) controllers for both current and speed control loops. Additionally, a parameter variation analysis is conducted to enhance the proposed methodology. The validity region for the design procedure is presented, ensuring that for any wide speed variation of the machine, loop gains are properly tuned. One of the main advantages of the proposed methodology is that it provides a fast, reliable, and accurate technique for implementing IPMSM drive systems. Results from a controller Hardware-in-the-Loop (C-HIL) setup with an external microcontroller are presented. The comprehensive design approach is validated under two different IPMSM parameter sets, demonstrating its effectiveness. © 2013 IEEE.

关键词： Vector control (Electric machinery)

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Robust control of Feeding Speed in Coal Seam Drilling process Considering Borehole Friction

Robust Control of Feeding Speed in Coal Seam Drilling Proces...

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2024 China automation Congress, CAC 2024

作者： Liu, Xiao Chen, Luefeng Lu, Chengda Fan, Haipeng Wu, Min Pedrycz, Witold School of Automation The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems The Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada Systems Research Institute Polish Academy of Sciences Warsaw00-901 Poland Department of Computer Engineering Istinye University Sariyer Istanbul34396 Turkey

ISBN: (纸本)9798350368604

During the coal seam drilling process, the drill string is subject to compressive deformation, compounded by unpredictable variations in formation hardness and borehole wall friction, leading to challenges in maintaining a stable feeding speed. This paper presents a novel approach by introducing uncertain parameters to describe the effects of formation hardness and borehole wall friction. Drill string axial movement model is modeled as a polyhedral system based on a lumped parameter representation. To meet industrial performance requirements, we design a robust H∞ controller to achieve consistent feeding speed control. Our simulation results demonstrate the controller’s effectiveness in ensuring system stability despite fluctuations in formation hardness and drill string friction. © 2024 IEEE.

关键词： Coal deposits

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Semi-Supervised process Data Regression and Application Based on Latent Factor Analysis Model

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IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Zheng, Junhua Liu, Yangxuan Liu, Yi Hou, Beiping Yao, Yuan Zhou, Le Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

This article investigates the problem of modeling regression with labeled and unlabeled data samples commonly found in industrial processes. By incorporating additional information on unlabeled data samples, a new semi-supervised latent factor analysis model is developed. Compared with the purely supervised regression models which can only use the information of labeled dataset, the semi-supervised model can efficiently extract useful information for improvement of the regression performance. Furthermore, the proposed basic semi-supervised model has been extended to a mixture form, which is capable of describing data from more complex processes. For predictive modeling for key/mass variables, two soft sensors are constructed based on the semi-supervised models. Then, three case studies are used to evaluate the performance of the proposed soft sensing methods. © 2023 IEEE.

关键词： Regression analysis

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Towards influence centrality: where to not add an edge in the network?

arXiv

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arXiv 2024年

作者： Shrinate, Aashi Tripathy, Twinkle Control and Automation specialization of the Department of Electrical Engineering Indian Institute of Technology Kanpur Uttar Pradesh Kanpur208016 India

In this work, we consider a strongly connected group of individuals involved in decision-making. The opinions of the individuals evolve using the Friedkin-Johnsen (FJ) model. We consider that there are two competing ‘influencers’ (stubborn agents) vying for control over the final opinion of the group. We investigate the impact of modifying the network interactions on their respective control over the final opinions (influence centrality). We use signal flow graphs (SFG) to relate the network interactions with the influence that each ‘influencer’ exerts on others. We present the sufficient conditions on the edge modifications which lead to the increase of the influence of an ‘influencer’ at the expense of the other. Interestingly, the analysis also reveals the existence of redundant edge modifications that result in no change in the influence centrality of the network. We present several numerical examples to illustrate these results. © 2024, CC BY-NC-ND.

关键词： Signal flow graphs

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Multimodal process Monitoring Based on Dynamic Extended K-means-VAE-RF

Multimodal Process Monitoring Based on Dynamic Extended K-me...

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第35届中国控制与决策会议

作者： Shiwei Su Kaixiang Peng Xueyi Zhang Key Laboratory for Advanced Control of Iron and Steel Process of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing

With the development of customization and flexibility of manufacturing industry,intelligent manufacturing process gradually presents multimodal characteristics,which are reflected in the strong coupling,nonlinear,multi working conditions and other characteristics of the *** this paper,a multi-modal process monitoring method based on dynamic expansion is *** view of the dynamic characteristics of process data,the process data is dynamically expanded through the amplification matrix,and then the multi-modal process data is modal divided through the improved K-means *** divided multi-modal process data is monitored using Variational Autoencoder,and relevant statistics and control limits are ***,the multi-modal process monitoring is constructed by introducing the method of random forest for modal *** validity of the algorithm is verified by real data of steel rolling process.

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Distributed Optimization with Efficient Communication, Event-Triggered Solution Enhancement, and Operation Stopping

arXiv

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arXiv 2025年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. Guangzhou China Department of Computer Science and Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Finland Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden Digital Futures United Kingdom

In modern large-scale systems with sensor networks and IoT devices it is essential to collaboratively solve complex problems while utilizing network resources efficiently. In our paper we present three distributed optimization algorithms that exhibit efficient communication among nodes. Our first algorithm presents a simple quantized averaged gradient procedure for distributed optimization, which is shown to converge to a neighborhood of the optimal solution. Our second algorithm incorporates a novel event-triggered refinement mechanism, which refines the utilized quantization level to enhance the precision of the estimated optimal solution. It enables nodes to terminate their operation according to predefined performance guarantees. Our third algorithm is tailored to operate in environments where each message consists of only a few bits. It incorporates a novel event-triggered mechanism for adjusting the quantizer basis and quantization level, allowing nodes to collaboratively decide operation termination based on predefined performance criteria. We analyze the three algorithms and establish their linear convergence. Finally, an application on distributed sensor fusion for target localization is used to demonstrate their favorable performance compared to existing algorithms in the literature. © 2025, CC BY.

关键词： Dynamic programming

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Double layer scheduling mechanism in Virtual power plant

Double layer scheduling mechanism in Virtual power plant

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2023 International Conference on Future Energy Solutions, FES 2023

作者： Cui, Huahu Zhang, Qian Wang, Daxin Zhang, Weishi Qi, Hui Fan, Lei Anhui University School of Electrical Engineering and Automation Anhui Key Laboratory of Industrial Energy-Saving and Safety Hefei China Ministry of Education Anhui University School of Electrical Engineering and Automation Engineering Research Center of Power Quality Hefei China Anhui Power Exchange Center Co. Ltd Transaction Department Hefei China Anhui University Anhui Collaborative Innovation Center of Industrial Energy-Saving and Power Quality Control Hefei China

ISBN: (纸本)9798350332308

Aiming at the problems of operation economy and stability of power systems with a high proportion of renewable energy, this paper proposes a two-layer optimal scheduling model based on internal trading of the VPP (Virtual power plant) energy layer. Firstly, the users participating in the smart contract and the VPP within the region are regarded as different interest subjects. And the maximum opportunity benefit of users is taken as the internal optimization goal. Secondly, taking the overall benefit maximization of the VPP as the overall optimization objective,. Thus, a two-layer optimal scheduling model including energy storage is established, and the multi-objective particle swarm optimization algorithm was applied to solve the problem. The local consumption of new energy is taken as the criterion, and the price of some local consumption energy is determined by the bidding mechanism of producers and sellers. Finally, the thermal power units are used as auxiliary units. In the two scenarios with or without energy storage, comparative tests are made on the internal trading of the energy layer of VPPs. The optimal scheduling results show that the internal trading of the energy layer of VPP contributes to the local consumption of new energy and improves the overall internal income level of VPP. © 2023 IEEE.

关键词： Virtual Power Plants

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A Knowledge-driven Cross-modal Memory Network for Radiology Report Generation

A Knowledge-driven Cross-modal Memory Network for Radiology ...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical processes, SAFEprocess 2023

作者： Fan, Junyan Wang, Jing Zhou, Meng Zhang, Yanzhu Shi, Mingyu North China University of Technology School of Electrical and Control Engineering Beijing China Shenyang Ligong University School of Automation and Electrical Engineering Shenyang China The Fourth Affiliated Hospital of China Medical University Eye Hospital of China Medical University The Key Laboratory of Lens in Liaoning Province Shenyang Department of Ophthalmology China

ISBN: (纸本)9798350337754

In previous studies, most work focused on generating high-quality reports by smoothing the alignment between cross-modal mappings. However, a common problem with current radiology report generation methods is that they ignore the interactions and connections between various medical findings that are critical to medical discovery. To overcome this problem, we propose a knowledge-driven cross-modal memory network. The network is built by data mining clinical reports and constructing knowledge graphs and their corresponding adjacency matrices based on the mined a prior knowledge. Combining information after graphical interaction through a cross-modal memory network with a knowledge graph adjacency matrix. Finally the Transformer generates a full report. Experiments have demonstrated that reports generated from cross-modal memory network models that incorporate prior knowledge are more clinically informative. © 2023 IEEE.

关键词： Knowledge graph

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Resilient Cooperative control of Multiple DC Microgrids With Interconnection Networks Against Cyber Attacks

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 116-126页

作者： Xiao, Feng Liu, Shiyu Wei, Bo Fang, Fang Qin, Jiahu North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources Beijing102206 China North China Electric Power University School of Control and Computer Engineering Beijing102206 China North China Electric Power University New Energy Generation National Engineering Research Center Beijing102206 China University of Science and Technology of China Department of Automation Hefei230027 China

The two control objectives of voltage regulation and precise current sharing are conflicting in multi-bus DC microgrids. In this paper, a distributed control strategy is proposed, and it can achieve accurate current sharing and regulate the voltage of a critical node to the rated value. However, such a distributed control system is susceptible to potential cyber attacks that could deteriorate microgrids performances by corrupting communication links or actuators. To overcome these difficulties, we design the interconnected communication networks to establish a resilient cooperative system of multiple microgrids against unknown bounded injection attacks. The proposed resilient control strategy can achieve the control objectives of maintaining voltage regulation and current sharing within each microgrids under different operating conditions, and the interconnected system consisting of multiple microgrids cooperates to mitigate the adverse effect of cyber attacks. The dynamics and stability of the overall close-loop system of the DC microgrids are analyzed, in the present or absent of cyber attacks. Simulation results validate the effectiveness of the proposed approach in two 4-bus DC microgrids. © 2023 IEEE.

关键词： Cyber attacks

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