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Real-time drone detection framework based on advanced texture feature extraction and pattern recognition model using GUI

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Neural Computing and Applications 2025年第5期37卷 3435-3454页

作者： Hussen, Noha Salem, Mofreh Eldesouky, Ali I. Sakr, Noha Elghamrawy, Sally Computers and Control Systems Engineering Department Mansoura University Mansoura Egypt Computer Engineering Department Misr Higher Institute for Engineering and Technology Mansoura Egypt

The increasing prevalence of drones has raised significant concerns regarding their potential for misuse in activities such as smuggling, terrorism, and unauthorized access to restricted airspace. Consequently, the development of robust and efficient drone detection systems has become paramount. Traditional detection methods such as radar and acoustic sensors have limitations in detecting small drones and can be costly to implement. This can lead to lower detection rates and increased security breaches and safety concerns. However, prevailing methodologies often falter in achieving real-time detection with requisite precision and efficacy, particularly within complex operational environments. Motivated by the imperative to surmount these challenges, our research endeavors to introduce a pioneering real-time drone detection framework. Our study encapsulates several seminal advancements. Firstly, we proffer a groundbreaking framework that synergizes advanced integration technique based on texture feature extraction and pattern recognition techniques for real-time drone detection to increase accuracy to detect drones in different conditions such as bad weather and low resolution. Secondly, we introduce an intuitive graphical user interface, enhancing the usability and accessibility of the system in real-time scenario. Lastly, through exhaustive evaluation and comparative analysis, we substantiate the superior performance of our framework in terms of accuracy, precision, and real-time detection capabilities compared to conventional DDS methodologies. Its stability and effectiveness render it a compelling solution for security-focused entities, notably those within air force and military systems. Our experimental results reveal a commendable accuracy rate of 97%, affirming the reliability and precision 98% and recall parameter 98% of our framework in accurately identifying and detecting drones, thus surpassing recent models in the field. © The Author(s), under exclusive

关键词： Graphical user interfaces

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Data-driven output regulation control for constrained linear systems

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Science China(Information Sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Model-Free Current Predictive control for PMSMs With Ultra-Local Model Employing Fixed-Time Observer and Extremum-Seeking Method

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IEEE Transactions on Power Electronics 2025年第8期40卷 10682-10693页

作者： Lin, Xinpo Liu, Jianxing Liu, Zhuang Gao, Yabin Peretti, Luca Wu, Ligang Harbin Institute of Technology Department of Control Science and Engineering Weihai264209 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China KTH Royal Institute of Technology Division of Electric Power and Energy Systems Stockholm10044 Sweden

Conventional model predictive current control of permanent magnet synchronous machines (PMSMs) relies heavily on a precise mathematical model, which may be challenging to obtain in certain cases. To address this issue, this paper proposes a model-free predictive current controller for PMSMs. Specifically, the dynamic model of the motor currents is represented using two ultra-local models, which express the derivatives of a controlled output as the sum of an amplified control input and an unknown offset term. All system parameters, nonlinear terms, and unmodeled dynamics are encapsulated into two offset terms. Online estimation of these two offset terms is performed using a second-order fixed-time convergence observer without requiring exact knowledge of the system parameters in advance. In contrast to both the linear extended state observer and the super-twisting observer, the fixed-time observer enhances convergence speed while concurrently sustaining minimal chatting. To get rid of the need for model rated parameters, an extremum-seeking approach is utilized to tune the control gains in the ultra-local model, where the amplitude of the disturbance item in extremum-seeking approach is adaptively attenuated, resulting in effective reduction of the fluctuations of both the control gains and PMSM's currents in steady state. Subsequently, a predictive controller is designed using this ultra-local model. Finally, the effectiveness and advantages of the proposed control scheme are confirmed through experimental results. © 1986-2012 IEEE.

关键词： Permanent magnets

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GY-YOLO: ghost separable YOLO for pedestrian detection

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Neural Computing and Applications 2025年 1-27页

作者： Elhenidy, Ali M. Labib, Labib M. Haikal, Amira Y. Saafan, Mahmoud M. Computers and Control Systems Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt Faculty of Engineering Mansoura National University Gamasa Egypt

In recent years, there has been impressive development in human detection. The main challenge in pedestrian detection is the training data. To assess detectors in crowd scenarios more effectively, a novel dataset in this study called the HEP dataset (Hybrid Egyptian Pedestrian dataset) is introduced. The HEP dataset is extensive, has comprehensive annotations, and is highly diverse. The dataset images are collected by two different means. Most of the images are collected from different mobile cameras for people crossing the street in high crowded streets in Egypt, and the rest of the images are collected from the web. That is why the dataset is called hybrid. The collected dataset is more suitable for pedestrian detection as the whole images focus on pedestrian scenarios for people outdoors crossing the street. This outperforms the previous benchmarks such as CrowdHuman and WiderPerson which collect data from the web and surveillance cameras with lots of images for indoor people. GS-YOLO also is proposed to address the real-time performance and the occlusion in the crowd scenes issues. GS-YOLO is a novel pedestrian detection model that utilizes efficient Ghost and depth separable convolution modules. GS-YOLO replaces all the convolution layers in the backbone and the head of the original YOLOv8 with Ghost and depth separable modules, respectively. A deformable to-features module is proposed to enrich features for the different feature pyramid networks. GS-YOLO is trained and tested over the collected dataset and other benchmarks like CrowdHuman and WiderPerson datasets. GS-YOLO achieves competitive results over the state-of-the-art models such as YOLOv5 and YOLOv8. GS-YOLO achieves 92.8% mAp on the HEP dataset, while YOLOv5 achieves 90.3% mAp and YOLOv8 achieves 91.1% mAp. © The Author(s) 2025.

关键词： Computer vision Deep learning Pedestrian detection YOLO

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Development and Application of Coverage control Algorithms: A Concise Review

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14906-14927页

作者： Cheng, Bin He, Mingyuan Zhu, Zhongpan He, Bin Chen, Jie Tongji University Department of Control Science and Engineering Shanghai201804 China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai201203 China

Coverage control is a foundational domain within multi-agent systems, which has recently undergone substantial advancements. Model-based and optimization-based control methods have achieved new breakthroughs and applications, while data-driven and learning-based algorithms in coverage control have also yielded significant results. This review examines the evolution and application of coverage control algorithms in multi-agent systems. Moreover, this review then focuses on how contemporary algorithms build on traditional control strategies and integrate cutting-edge data-driven and adaptive learning techniques. Finally, it explores potential future directions, emphasizing the importance of interdisciplinary approaches in overcoming existing challenges and seizing new opportunities in coverage control deployment. This review aims to be a valuable resource for researchers and practitioners, guiding continued exploration in this field. Note to Practitioners - This work was motivated by the need to provide an overview of the development and research of existing multi-agent coverage control algorithms. Different application scenarios and constraints require different methods of multi-agent coverage control, each with varying efficiencies. For researchers and practitioners, deciding which coverage control method to use in specific scenarios, while considering practical constraints such as energy limitations, can be challenging. Therefore, this work offers an overview of existing multi-agent coverage control algorithms and suggests potential application scenarios. This review serves as a comprehensive reference for researchers and practitioners in the field, helping them identify suitable solutions to ensure efficient coverage. © 2004-2012 IEEE.

关键词： Learning algorithms

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Input-Restricted Stability of Continuous and Discrete Time Nonlinear Feedback systems

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IEEE Transactions on Automatic control 2025年第5期70卷 3149-3164页

作者： Hilborne, Peter Lanzon, Alexander Khong, Sei Zhen University of Manchester Control Systems Centre Department of Electrical and Electronic Engineering School of Engineering ManchesterM13 9PL United Kingdom National Sun Yat-sen University Department of Electrical Engineering Kaohsiung80424 Taiwan

In this article, we develop the concept of input-restricted stability, which determines whether a feedback interconnection remains stable only for inputs in a given subset of all possible inputs in a specified signal space. Graph separation concepts and continuity are employed to derive an input-restricted feedback stability theorem, which guarantees input-restricted stability of a feedback interconnection if both systems in the interconnection fulfil some given criteria related to their input–output relationships. Significantly, this result is applicable to both continuous and discrete time systems, unlike many existing local stability results. This theorem is then specialized into simpler-to-compute corollaries and expanded to additional theorems which provide useful additional insights. This article ends with two salient specializations of key results developed herein: one is a type of input-restricted small-gain stability theorem with one system bounded by a linear gain and the other by a quadratic gain;and the other is a type of input-restricted passivity theorem. For both of these specializations, which are not stable for all energy bounded inputs, an example is provided where the feedback interconnection is shown to be stable when the energy of exogenous inputs is below a given threshold. © 1963-2012 IEEE.

关键词： Continuous time systems

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Open-loop equilibrium seeking in two-agent noncooperative linear-quadratic dynamic game with asymmetric horizon length

Open-loop equilibrium seeking in two-agent noncooperative li...

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作者： Wasa, Yasuaki Tanaka, Taichi Hayakawa, Tomohisa Department of Electrical Engineering and Bioscience Waseda University Tokyo Japan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo Japan

This article proposes an iterative-based algorithm for open-loop equilibrium seeking in a two-agent noncooperative dynamic game. The finite-horizon dynamic games handled in almost all existing articles assume the common prediction horizon length. From the viewpoint of divergence and differences in personal values, it is socially rational to solve the equilibrium of the games with asymmetric prediction horizon length. We thus propose an open-loop equilibrium-seeking algorithm without the private knowledge of the other agent's horizon information through a receding-horizon linear-quadratic game. Our proposed algorithm is based on iterative optimization. Each agent obtains its own best response control strategy while estimating the other agent's state feedback gain from the state information and guaranteeing the stability of the whole system. We also discuss the performance of the proposed equilibrium-seeking algorithm through numerical examples. © 2023 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd.

关键词： Iterative methods

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Equilibria Computation of the Weakest-Link Discrete Colonel Blotto Games

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IEEE control systems Letters 2025年 9卷 132-137页

作者： Ravi Ibrahim, Adrianto Nugraha, Yurid E. Tsukuba 305-0051 Japan Institut Teknologi Sepuluh Nopember Department of Systems and Control Engineering Surabaya60111 Indonesia

A class of Colonel Blotto Games between two agents over multiple locations are discussed. In this letter, we consider the scenario where one of the agents wins whenever she allocates more resources in all locations. We derive a theoretical result showing that mixed Nash equilibria in such games could be computed in polynomial time. © 2017 IEEE.

关键词： Computational methods

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Fault-Tolerant Soft Sensor Modeling Based on a Two-Dimensional Group Distributionally Robust Optimization Framework

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IEEE Transactions on Automation Science and engineering 2025年 22卷 14396-14406页

作者： Zhang, Xiangrui Song, Chunyue Zhao, Jun Huang, Biao College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Industry Intelligence and Systems Engineering Hangzhou310027 China University of Alberta Department of Chemical and Materials Engineering EdmontonABT6G 1H9 Canada

In industrial automation and intelligence, fault tolerance mechanisms have always been an attractive topic. To develop soft sensors with fault tolerance for different types of faults and unforeseen new faults, this article proposes a two-dimensional group distributionally robust optimization (2D-GDRO) framework for fault-tolerant soft sensor modeling. We propose to describe the potential distributions of new fault conditions with an uncertainty set and optimize the soft sensor model by minimizing the worst-case risk over the uncertainty set. Considering the restricted representation range of the uncertainty set constructed directly from a mixture distribution of a limited number of existing fault conditions in the training set, a two-dimensional uncertainty set is designed at the group dimension and the sample dimension. To efficiently train a fault-tolerant soft sensor within the 2D-GDRO framework, we introduce a triple-interleaved optimization algorithm. This algorithm integrates mini-batch stochastic gradient descent, exponentiated gradient ascent, and group-wise SoftMax techniques. Finally, the fault tolerance of the 2D-GDRO framework based soft sensor is verified using the Tennessee-Eastman process and the real three-phase flow facility. The experimental results show that 2D-GDRO outperforms other training frameworks in average soft sensing accuracy under new fault conditions. © 2004-2012 IEEE.

关键词： Stochastic systems

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Model-Free Predictive control in Anaerobic Digestion Wastewater Treatment

Model-Free Predictive Control in Anaerobic Digestion Wastewa...

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2025 SICE International Symposium on control systems, SICE ISCS 2025

作者： Pratvittaya, Jiravit King Mongkut's University of Technology Thonburi Department of Control Systems and Instrumentation Engineering Bangkok Thailand

ISBN: (纸本)9784907764852

Anaerobic digestion is a wastewater treatment method that utilizes bacterial decomposition to convert organic matter into biogas, which provides both environmental and economic benefits. However, controlling biogas production in anaerobic digestion systems poses significant challenges due to the complexity and non-linearity of the digestion process. This study explores the application of model-free predictive control for anaerobic digestion systems, utilizing only inputoutput data without using mathematical models as in conventional control approaches. Previous research has demonstrated the applicability of this approach for nonlinear systems, particularly in multi-input, multi-output nonlinear systems. In this study extends the methodology to controlling in methane production of anaerobic digestion systems, evaluating its effectiveness through numerical simulations. © 2025 The Society of Instrument and control Engineers.

关键词： Anaerobic digestion

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