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International Carpathian control Conference (ICCC)

作者： Iulian Vasiliev Laurentiu Luca Marian Barbu Ramon Vilanova Sergiu Caraman Department of Automation and Electrical Engineering Faculty of Automation Computers Electrical and Electronic Engineering Galati Romania Department of Automation Systems and Advanced Control Research Autonomous University of Barcelona Barcelona Spain

A model of a sewer network for a medium city located in Easter Romania with 250,000 inhabitants is presented in the paper. The model was developed using BSM Sewer software package. An influent was also determined considering the 5 collecting areas and defined on a time- horizon of 28 days. The influent has the following components: a domestic one calculated using the average wastewater production of each inhabitant with specific loads and considering daily, weekly and yearly variations, a pluviometric one proportional to the collecting area surface that includes a rain event and a storm one and an industrial influent (considered only for the 5 th collecting area). The model was tested in different operating conditions of the sewer network considering three operating points given by the values of the valve opening and pumps flows at the tank outlets. The results were analyzed based on 10 performance indicators implemented by researchers from Lund University for BSM Sewer. They showed the need for an optimization of the operating regime of the sewer network in terms of volume and quality of discharged water.

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Comparative Analysis of Pharmacokinetic-Pharmacodynamic Models for Propofol and Remifentanil Using Model Predictive control

Comparative Analysis of Pharmacokinetic-Pharmacodynamic Mode...

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European control Conference (ECC)

作者： A. R. Ynineb H. Farbakhsh G. Ben Othman Y. Wahlquist I. R. Birs E. Yumuk C. I. Muresan R. De Keyser D. Copot C. M. Ionescu M. Neckebroek Department of Electromechanics Systems and Metal Engineering Research Group on Dynamical Systems and Control Ghent University Gent Belgium Department of Automatic Control Lund University Lund Department of Automation Technical University of Cluj-Napoca Cluj-Napoca Romania Department of Control and Automation Engineering Istanbul Technical University Maslak Istanbul Turkey Department of Anesthesia Ghent University Hospital Ghent Belgium

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This study aims to compare the effectiveness of different Pharmacokinetic-Pharmacodynamic (PK-PD) models for administering Propofol and Remifentanil, two critical agents in anesthesia. Initially, different PK models were introduced: one for Propofol based on the Schnider model and another for Remifentanil using the Minto model. Alternatively, both drugs were modeled using the Eleveld models. The PK-PD models were integrated into a closed-loop control system using model predictive control (MPC) with disturbances to control the Bispectral index (BIS) and the Richmond Agitation Sedation Scale (RASS). The methodology involved simulating the anesthetic agents in the open-source patient simulator (2 inputs, 2 outputs) with 12 patient datasets in a controlled environment to simulate the patient response variability, allowing for a detailed analysis of the model's performance in maintaining optimal drug concentrations. The primary focus was on the system's ability to adapt to surgical disturbances, a key challenge in anesthesia management, and whether a different modeling of drugs can have an impact on their effects. The results indicated significant differences in the performance of the two models configurations. The Eleveld model for Propofol showed less usage of drugs to maintain the desired BIS value. Concluding that this comparative analysis offers a valuable reference for selecting appropriate modeling approaches in the development of advanced control strategies in anesthesia.

关键词： Drugs Analytical models Adaptation models Surgery Europe Predictive models Anesthesia

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DYNAMIC STIFFNESS ANALYSIS OF ELECTRO-HYDRAULIC SERVO-controlLED HYDRAULIC MOTOR

DYNAMIC STIFFNESS ANALYSIS OF ELECTRO-HYDRAULIC SERVO-CONTRO...

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2024 CSAA/IET International Conference on Aircraft Utility systems, AUS 2024

作者： Chen, Taiqi Wu, Shuai Wei, Renlei Li, Chuandong Qin, Mingyuan Chu, Bing Yang, Yuliang Luo, Jianing School of Automation Science and Electrical Engineering Beihang University Beijing100191 China National Key Laboratory of Aircraft Integrated Flight Control Beihang University Beijing100191 China Key Laboratory of Advanced Aircraft Systems Beihang University Ministry of Industry and Information Technology Beijing100191 China AVIC Shenyang Aircraft Design and Research Institute Shenyang110087 China

Electro-hydraulic servo control systems find widespread applications in aerospace, engineering machinery, and robotics, where they are integral to maintaining the performance and safety standards of aircraft. This study focuses on examining the dynamic stiffness properties of hydraulic motors in these systems and analyzes how different parameters affect dynamic stiffness. Dynamic stiffness describes an actuator's rigidity and response characteristics in motion control scenarios, reflecting the stability and performance of aircraft actuators under complex dynamic operational conditions more accurately than static stiffness. The study employs modular modeling to establish a mathematical model for dynamic stiffness, revealing that the servo valve inherent frequency, damping coefficient, pipeline volume, and hydraulic oil bulk modulus exhibit low sensitivity. Proportional gain, servo valve gain, and servo valve flow coefficient show consistent sensitivity curves, indicating a strong correlation. Conversely, the leakage coefficient and hydraulic motor displacement sensitivity negatively correlate with frequency, while hydraulic motor inertia, damping coefficient, and gearbox reduction ratio positively correlate with frequency. These insights enhance the understanding of parameter impacts, aiding in the design and optimization of high-power-to-weight ratio hydraulic systems for aerospace applications. © The Institution of Engineering & Technology 2024.

关键词： Sensitivity analysis

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H∞ consensus for stochastic Markov jump multi-agent systems with imperfect time-varying transition probabilities and multiplicative noise

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Applied Mathematics and Computation 2023年 436卷

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

In this paper, the H∞ consensus control problem for Markov jump multi-agent systems with imperfect time-varying transition probabilities is studied. Both the transition probability matrix and the higher-level transition probability matrix are considered to be partly unknown. What's more, the multiplicative noise is considered in the model to describe the factors from the changing environment. Sufficient conditions about state feedback controllers are derived by less linear matrix inequalities (LMIs) and are more convenient to program compared with the previous works. At last, the simulations are supplied to illustrate the effectiveness of the conclusions. © 2022

关键词： Multi agent systems

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Contrastive Conditional Adversarial Autoencoder with Class-specific Forces for Imbalanced Open-set Fault Detection

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IEEE Transactions on automation Science and Engineering 2025年 22卷 15757-15767页

作者： Zuo, Zhonglin Meng, Tao Li, Zheng Zhang, Hao Liu, Tong Chen, Zhansheng Pang, Zhibo Zhejiang University College of Control Science and Engineering Hangzhou310027 China Zhejiang University School of Aeronautics and Astronautics Hangzhou310027 China Hainan Institute of Zhejiang University Sanya572025 China Chongqing University School of Automation Chongqing400044 China University of Sheffield Department of Computer Science SheffieldS1 4DP United Kingdom Shanghai Aerospace Space Technology Co. Ltd Shanghai201109 China ABB Corporate Research Sweden Department of Automation Technology Vasteras Sweden KTH Royal Institute of Technology Department of Intelligent Systems Stockholm Sweden

In real-world industrial scenarios, fault detection faces the widely recognized challenge of data imbalance, which not only refers to the scarcity of fault data but also includes the imbalance in healthy data. This article is concerned with imbalanced open-set fault detection (IOSFD), a practical yet challenging scenario in industrial applications where multiple healthy operating conditions and multiple fault types are imbalanced. In this article, we propose a new contrastive conditional adversarial autoencoder for IOSFD. It constructs an end-to-end unified model based on multi-class known healthy and faulty data to address the reliance of traditional methods on fault samples, while optimizing with class-specific weighted forces to ensure equal attention to imbalanced known classes. Input and feature reconstruction conditioned on operating modes are utilized to learn a compact decision plane and achieve both unknown fault detection and known data classification. Significantly, we formulate the optimization objective of conditional reconstruction based on contrastive learning and introduce adversarial training to further enhance the model’s performance. The effectiveness of the proposed method is validated through real-world pipeline leak detection and Tennessee-Eastman multi-fault detection. © 2004-2012 IEEE.

关键词： Contrastive Learning

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli Dong Hongjian Liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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Accurate Identification and Localization of Transmission Lines under Complex Lighting for Distribution Network Power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

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2024 China automation Congress, CAC 2024

作者： Liu, Tianhe Chen, Xin Hu, Chenyu Jian, Xu Li, Shengzu Wang, Gang 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 Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company 430070 China

ISBN: (纸本)9798350368604

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an "eye-on-hand" configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within ±4mm, outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots. © 2024 IEEE.

关键词： Binocular vision

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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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Chinese automation Congress (CAC)

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

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

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.

关键词： Drilling Solid modeling Accuracy Torque Geology Transforms Reliability engineering Data models Real-time systems Robustness

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Distributed Power Source Planning Based on Improved Particle Swarm Optimization

Distributed Power Source Planning Based on Improved Particle...

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Power and Electrical Technology Conference (APET), Asia

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

ISBN: (数字)9798350367690

ISBN: (纸本)9798350367706

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.

关键词： Profitability Voltage Distributed power generation Power system reliability Planning Security Reliability Particle swarm optimization Optimization Testing

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Fault-Tolerant Model Predictive Load Frequency control for Power systems with Electrolytic Aluminum Load Under New Event-triggered Mechanism

Fault-Tolerant Model Predictive Load Frequency Control for P...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Shisen Zhou Ziqian Wang Xiongbo Wan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

In this paper, the problem of event-based fault-tolerant model predictive load frequency control is investigated for the power system where the electrolytic aluminum load participates in frequency modulation and actuator faults. A dynamic event-triggered mechanism containing an internal dynamic variable (IDV) and an adjustable variable is designed to reduce the data transmission burden. The fault-tolerant model predictive control (FTMPC) problem is expressed as a "min-max" optimization problem (OP). According to the Lyapunov-like function that depends on the IDV, an auxiliary OP with constrained linear matrix inequalities is constructed. By solving the auxiliary OP, the FTMPC controller gains that ensure the input-to-state stability of the closed-loop system can be obtained. The effectiveness of the proposed algorithm is verified through a simulation example.

关键词： Fault tolerance Actuators Aluminum Fault tolerant systems Power system dynamics Power system stability Predictive models

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