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New Class Detection in Network Traffic Classification Using Confidence Information Embedded Cascade Structure

IEEE Transactions on Network Science and engineering 2025年第3期12卷 1692-1706页

作者： Lu, Haotian Dong, Yuning Wu, Zhiyuan Wei, Hua-Liang Lu, Guanming Nanjing University of Posts and Telecommunications School of Communications and Information Engineering Nanjing210003 China The University of Sheffield Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom

Network traffic classification plays an important role in network management. With continued emergence of new applications, classifiers need to deal with unknown classes in an open set environment. However, the available open set flow recognition methods cannot well balance the performance of new class detection and the fine-grained classification of known classes. Moreover, these methods could pursue high accuracy at the cost of the classification speed. To address these problems, this paper proposes an unknown network traffic detection method based on confidence (difference) and a cascade structure, by analyzing the confidence distributions of both the known and new classes. The proposed method works as follows. Firstly, it uses a cascade structure to detect new class samples (having high confidence) which are difficult to identify using existing methods;secondly, it employs the maximum confidence difference to classify the new and known classes. In order to better detect new classes with high confidence, an algorithm is designed to select the pseudo-negative samples from the unlabelled dataset with an adaptive threshold. The proposed method is evaluated on real-world datasets. The results show that compared with the state-of-the-art methods, the proposed method can significantly improve the overall accuracy and the classification latency is also greatly reduced. © 2013 IEEE.

关键词： Data accuracy

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Hybrid offshore wind turbines: control-oriented modeling approaches 6th

Hybrid offshore wind turbines: Control-oriented modeling app...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Ahmad, I. M’zoughi, F. Aboutalebi, P. Garrido, I. Garrido, A.J. Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Engineering School of Bilbao—EIB/BIE Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Bilbao Spain

ISBN: (纸本)9781032905570

In the pursuit of sustainable electricity generation from offshore wind and wave energy, the combination of Floating Offshore Wind Turbines (FOWTs) and Oscillating Water Columns (OWCs) has emerged as a promising solution to enhance the working lifespan of this kind of systems. This study introduces a control-focused modeling approach, using empirical data collected from the widely accepted FAST environment, to implement advanced control laws for these integrated platforms. Leveraging Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN), the research yields predictive models that effectively capture the platform pitch dynamics so as to optimize control strategies. By integrating advanced machine learning techniques, these approaches address the challenges of modeling floating offshore structures in dynamic environments. In this sense, the neuro-estimators developed in this study closely match the original plant results, offering researchers a straightforward way to implement complex control schemes that could hardly be implemented over the original non-linear system. © 2025 The Author(s).

关键词： Offshore wind turbines

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Voltage and power control for distributed generation units in islanded microgrids 6th

Voltage and power control for distributed generation units i...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Rouch, T. Bagheri M’zoughi, F. Aboutalebi, P. Ahmad, I. Garrido, A.J. Garrido, I. Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country Bilbao Spain

ISBN: (纸本)9781032905570

This article presents an optimized control strategy tailored for DC islanded microgrids, featuring a voltage controller based on mixed H2/H∞ state feedback using linear matrix inequalities (LMIs) and a power controller guided by droop characteristics. A polytopic modeling approach addresses system uncertainties and nonlinearities. The controller aims to stabilize the system, reject disturbances, equitably distribute power among distributed generation units (DGUs), and minimize energy consumption. Regional pole placement ensures welldamped transient responses. Simulation results demonstrate effective management of load perturbations and DGU disconnections, with a comparative analysis against an H∞ controller offering additional insights into performance. © 2025 The Author(s).

关键词： Microgrids

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Development of automatic Cartesian Robot Cannabis Seeder using LabVIEW 10

Development of Automatic Cartesian Robot Cannabis Seeder usi...

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10th International Conference on Digital Arts, Media and Technology and 8th ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Kosarat, Rujipan Sangwai, Keattipoom Wongjan, Anan Rajamangala University of Technology Lanna Faculty of Engineering Department of Software Engineering Chiangmai Thailand Rajamangala University of Technology Lanna Faculty of Engineering Department of Electronic Engineering and Automatic Control Systems Chiangmai Thailand

ISBN: (纸本)9798331543273

This article describes the invention of autonomous cannabis seeding equipment to reduce contamination and planting time. The automated cannabis seeder employs an NI myRIO control board to operate a y-axis stepper motor attached to a ball screw to move along the breadth of each row of 14 seed trays. Soil drilling and burial Drill all holes at the same depth. This promotes seed germination and lowers human-seed germ contamination. These 7 soil drill heads and 7 seeders use 3D printers to design and shape the workpiece. An 800-watt air pump smokes the cannabis seeds. Linear electric motors function in two rows in the z-axis. The buffer reverses the drowning process from row 14 to the first row, starting from the 3rd row and continuing through the final series of steps until 14 rows in the y-axis are complete. The hardware controls all program activities in LabVIEW. We tested the automated cannabis seeding machine 100 times on average, sowing cannabis seeds into 98 seed trays and dropping 93 seeds at 94.80% efficiency in 10.38 minutes. A 16 percent faster machine than human work is available. © 2025 IEEE.

关键词： Stepping motors

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A Zero-Sequence Current Analysis Approach for Rotating Machinery Fault Diagnosis of Induction Motor Drivetrain Based on Sparse Learning

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IEEE Transactions on Power Electronics 2025年第7期40卷 9800-9810页

作者： Liu, Zhao-Hua Long, Jun-Jie Wei, Hua-Liang Liu, Kan Zhang, Ying-Jie Li, Xiao-Hua Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China The University of Sheffield School of Electrical and Electronic Engineering Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Fault diagnosis of rotating machinery driven by induction motors has received increasing attention. Current diagnostic methods, which can be performed on existing inverters or current transformers of three-phase induction machines, have become a more economical and reliable alternative to vibration diagnostic methods. Existing references mainly focus on the stator current analysis of single-phase, but most single-phase current analysis methods utilize only a fraction of the total information accessible in the three-phase system. Field experience shows that zero-sequence current (ZSC) has more distinctive fault characteristics compared to single-phase current, and therefore it is better to use in mechanical fault detection and diagnostic tasks. This article proposes a novel sparse learning-based method for ZSC analysis for induction rotating motor drive fault diagnosis. First, it elaborates and compares the effectiveness of ZSC in revealing fault characteristics compared with single-phase current by analyzing the fault diagnosis mechanism of ZSC. In addition, the method proposes a correlation entropy-enhanced sparse learning method for the problem of high-frequency noise and interference in the ZSC signals, so as to enhance the learning of the features of the noise-containing signals. The diagnostic efficacy of the proposed method has been verified through experiments on two real datasets. © 1986-2012 IEEE.

关键词： Induction motors

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Small Signal Stability-Guaranteed Moving Target Defense Against Load Redistribution Attack On IoT-based Smart Grid

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IEEE Internet of Things Journal 2025年第11期12卷 17413-17429页

作者： Wang, Bingdong Zhang, Zhenyong Wang, Mufeng Liu, Mengxiang Ye, Rui Deng, Ruilong Zhang, Xin Guizhou University State Key Laboratory of Public Big Data College of Computer Science and Technology Guiyang550025 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Guizhou Power Grid Co. Ltd. Intelligent Operation Center China Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute of Industrial Control Technology Huzhou313000 China

Moving target defense (MTD) is a promising approach to defend against load redistribution attacks on the internet-of-things (IoT)-based smart grid networks by probing the distorted state estimates with the distributed flexible AC transmission system. However, existing studies mainly focus on optimizing the performance of MTD and ignore the safety effect of it on the system’s operation. In this paper, we fill this gap by deeply analyzing the effect of MTD on the small signal stability and aim to alleviate the negative impact and guarantee its defending performance simultaneously. Firstly, the stability is formally described using the eigenvalue sensitivity. The relationship between the MTD-induced perturbation (MTDper) and the stability criteria is derived. Secondly, a new indicator is proposed to measure the effectiveness of MTDper. Thirdly, a constrained optimization problem is formulated to compute the bound of MTDper for guaranteeing the small signal stability. In addition, a surprising finding is that the stability margin can be improved and enhanced by optimizing the value of MTDper without losing the MTD’s effectiveness. Finally, we evaluate the performance of MTDper and its impact on the small signal stability with extensive simulations on the IEEE 30-bus, 39-bus, and 68-bus test power systems. © 2014 IEEE.

关键词： Constrained optimization

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Fuzzy-Model-Based Fault-Tolerant control for Stochastic Re-Entrant Manufacturing systems

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IEEE Transactions on systems, Man, and Cybernetics: systems 2025年第5期55卷 3542-3556页

作者： Zhang, Kexin Gao, Qing Ding, Steven X. Lu, Jinhu Qiu, Jianbin Guo, Yige Beihang University School of Cyber Science and Technology Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Hangzhou Innovation Institute Beihang University Hangzhou310051 China Zhongguancun Laboratory Beijing100095 China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China Zhongguancun Laboratory Beijing China

This study addresses the problem of guaranteed cost fault-tolerant fuzzy control for multiline re-entrant manufacturing systems (RMSs) against stochastic disturbances and workstation faults. Initially, a nonlinear hyperbolic impulsive partial differential equation model is employed to describe the complex and hybrid dynamics of RMSs suffering from unexpected faults within the working stations, and then the corresponding approximation T-S fuzzy model is constructed. In what follows, with the aid of the parallel distributed compensation fuzzy control scheme, the main results of stability analysis and controller synthesis for the closed-loop re-entrant manufacturing control system are derived using a timer-dependent Lyapunov functional with spatio-temporal auxiliary variables. It is found that by means of the proposed fault-tolerant control approach, the RMS can be effectively and robustly driven to a desired production mode with steady feeding and production rates while the upper bound of a quadratic cost function is minimized. Finally, the effectiveness of the proposed control approach is validated through numerical simulations. © 2013 IEEE.

关键词： Fuzzy control

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System Optimal Routing and Distribution of Benefits on National Road Networks

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Transportation Research Procedia 2025年 82卷 2532-2545页

作者： Alexander Roocroft Giuliano Punzo Muhamad Azfar Ramli Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom Institute of High Performance Computing A*STAR Singapore

Rerouting drivers from selfish route choices to system-optimal traffic patterns has the potential to improve the performance of existing infrastructure. Previous research has looked into assessing the potential of rerouting through the empirical price of anarchy, a measure of network efficiency. However, studies using real-world measurements have been limited by methodological accuracy and network size. Also, they have lacked understanding of the spatial distribution of benefits from rerouting and the relationship with marginal external cost road charges that can be used for implementation. In this article, we create an accurate data-driven traffic assignment model of England's Strategic Road Network. We use it to calculate the national price of anarchy, which is found to be almost 1 implying gains from rerouting at the national scale are minimal and smaller than in other studies. The results show the distribution of rerouting benefits varies strongly with different network zones and demand profiles. This did not match the distribution of marginal external cost charges. Some zones have noticeable benefits from rerouting although the overall network benefit is small, however, these zones do not coincide with where the largest road charges have to be applied for system-optimal rerouting. These results have implications for rerouting implementation.

关键词： Strategic Road Network Empirical Price of Anarchy National Traffic Assignment

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Vibration Mitigation of Hybrid Oscillating Water Column-Floating Offshore Wind Turbine Using ANFIS-Based Airflow control 16th

Vibration Mitigation of Hybrid Oscillating Water Column-Floa...

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16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： M’zoughi, Fares Aboutalebi, Payam Ahmad, Irfan Rouch, Tahereh Bagheri Garrido, Izaskun Garrido, Aitor J. De La Sen, Manuel Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Po Rafael Moreno no. 3 Bilbao48013 Spain Automatic Control Group—ACG Institute of Research and Development of Processes IIDP Department of Electricity and Electronics Faculty of Science and Technology University of the Basque Country—UPV/EHU Bo Sarriena s/n Leioa48080 Spain

ISBN: (纸本)9783031817236

This paper introduces a novel approach to model and stabilize a Floating Offshore Wind Turbine (FOWT) by employing Oscillating Water Columns (OWC) as an active structural control system. The innovative concept involves designing a new floating barge-like platform with integrated OWCs on opposite sides of the platform to mitigate undesired oscillations of the system. These OWCs counteract the bending forces caused by wind on the tower and waves on the barge platform. To synchronize the opposing forces with the system’s tilting, a proposed Adaptive Neuro-Fuzzy Inference System-based airflow control strategy is employed. Through manipulation of the barge platform’s pitch angle, the ANFIS airflow control system adjusts the valves on either side, opening one and closing the other accordingly. Simulation results, compared with a standard FOWT demonstrate the effectiveness of the ANFIS airflow control. It is shown to be superior in reducing platform pitching and the fore-aft translation of the tower top. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Active Structural control Air Valve Airflow control ANFIS Barge Platform Floating Offshore Wind Turbine Oscillating Water Column

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Multi-agent Collision Avoidance Based on Buffered Voronoi Cells and B-Splines 16th

Multi-agent Collision Avoidance Based on Buffered Voronoi C...

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16th APCA International Conference on automatic control and Soft Computing, controlO 2024

作者： Dinh, Cong Khanh Prodan, Ionela Stoican, Florin LCIS Valence26000 France Department of Automatic Control and Systems Engineering National University of Science and Technology "Politehnica" Bucharest 313 Splaiul Independenţei Bucharest060042 Romania

ISBN: (纸本)9783031817236

This paper tackles the challenging issue of collision avoidance among multiple dynamical agents, a problem known for its non-convex nature and computational complexity. Our proposed solution involves decomposing the space into time-varying Voronoi cells with buffer zones, exploiting the versatility of B-splines to reconfigure trajectories when collisions are predicted. This approach is integrated into a Model Predictive control (MPC) framework, implemented in a distributed manner where agents communicate predicted control point sequences defining the B-spline curves. Through simulation testing across various scenarios, our approach demonstrates significant promise, paving the way for experimental validation and real-world applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Predictive control systems

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