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20th International Multi-Conference on systems, Signals and Devices, SSD 2023

作者： Talmoudi, Samia Ksouri, Moufida Lahmari Applied College Department of Computer Science University of Tabuk Tabuk Saudi Arabia University of Tunis El Manar National Engineering School of Tunis LR11ES20 Analysis Design and Control of Systems Laboratory Tunis1002 Tunisia

ISBN: (纸本)9798350332568

This paper is focused on uncertain fractional order systems. In this context, a new modelling approach of uncertain fractional order systems represented by an explicit fractional order interval transfer function is proposed. This approach is based, essentially, on multimodel approach. In fact, firstly, two new determination methods of models' library, inspired from the Kharitonov approach, are exposed. Then, we propose to compute the validity degree of each model of the obtained library, by optimizing a constrained least squares problem. The global model is, finally deduced by fusion of outputs of the different library' models. To prove its efficiency and its precision, the proposed approach is then compared to the approximation approach of Oustaloup through two simulation examples. © 2023 IEEE.

关键词： Transfer functions

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Optimal Sensor Placement for Full-Set TDOA Localization Accounting for Sensor Location Errors

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zhang, Chengjie Han, Xinyang Kong, He Ho, K.C. Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China University of Missouri Electrical Engineering and Computer Science Department ColumbiaMO65211 United States

The positioning accuracy of a signal source is influenced by where the sensors are deployed. Studies in the literature for the optimal sensor placement (OSP) of localization often ignore the presence of sensor position errors. In practice, however, it is impossible to place the sensors precisely at the desired locations. This work designs OSP by accounting for the presence of Gaussian sensor position errors that are independent and identically distributed (IID), with the full set of Time Difference of Arrival measurements corrupted by Gaussian IID noise. The criterion is the A-optimality equal to the trace of the source position Cramer-Rao Bound (CRB). We show that the presence of sensor position errors introduces a multiplication factor to the same criterion for the case without sensor position errors. The latter factor is dependent on the ratio of the sensor position error power to the range difference noise power but independent of the sensor positions, implying that the A-optimality OSP in the presence of sensor position errors is the same as in the absence. To our knowledge, this is the first time such results have been derived. Simulation studies validate the derived OSP, show the minimal OSP performance gap with sensor positioning error and without, and illustrate the better source localization accuracy by OSP. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

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Application of Petri Nets for Modeling Ore Flows to Create Dynamic Management and Quality control System in Mineral Resource Complexes

Application of Petri Nets for Modeling Ore Flows to Create D...

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2024 International Conference on Industrial Engineering, Applications and Manufacturing, ICIEAM 2024

作者： Larichev, Pavel Tynchenko, Vadim Nekrasov, Ivan Institute Of Computer Science And Telecommunications Reshetnev Siberian State University Of Science And Technology Information-Control Systems Department Krasnoyarsk Russia Bauman Moscow State Technical University Artificial Intelligence Technology Scientific And Education Center Moscow Russia Federal Univercity Laboratory Of Biofuel Composition Siberian Krasnoyarsk Russia

ISBN: (纸本)9798350395013

The article discusses the issue of creating a dynamic system for managing and monitoring the quality of ore flow in mineral resource complexes using simulation modeling. The purpose of this study is to adapt the mathematical apparatus of Petri nets to such modeling. The article describes the choice and justification of the simulation modeling apparatus and provides a conceptual representation of the ore flow model in the form of an adaptation of a continuous Petri net. An architectural solution is proposed that covers a number of processes, such as geological exploration, mining, moving loads in the business processes of enterprises, but also to support the rock mass. The proposed architecture is being coordinated with information systems and software and hardware of mining enterprises, which makes it possible to identify data needs for the formation of technical specifications for the correction of business processes. The proposed control system will make it possible to implement simulation modeling both in model and real time for timely and adequate assessment of the progress of work being carried out and clarifying the reasons for the lag behind planned schedules using a Petri net. © 2024 IEEE.

关键词： Petri nets

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Estimating the Sensitivity of Microoptoelectromechanical Micro-g Accelerometer 23

Estimating the Sensitivity of Microoptoelectromechanical Mic...

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23rd IEEE International Conference of Young Professionals in Electron Devices and Materials, EDM 2022

作者： Barbin, Evgenij S. Nesterenko, Tamara G. Koleda, Aleksej N. Shesterikov, Evgeniy V. Kulinich, Ivan V. Sheyerman, Fedor I. The Tomsk State University of Control Systems and Radioelectronics Laboratory of Radiophotonics Tomsk Russia Institute of Optics and Atmosphere Siberian Branch of the Russian Academy of Sciences Laboratory of Intelligent Computer Systems Tomsk Russia National Research Tomsk Polytechnic University Division for Electronic Engineering Tomsk Russia

ISBN: (纸本)9781665498043

The article studies a MOEMS-accelerometer with an optical measuring element based on an optical tunneling effect intended for measuring micro-g accelerations. The work estimates the sensitivity threshold of the accelerometer based on the Noise Equivalent Acceleration, which is stipulated by thermal Brownian motion of molecules, noises of a laser and photodiode. Shot noise has the largest effect on the MOEMS-accelerometer noise threshold and depends on its mechanical properties. The general sensitivity of the MOEMS-accelerometer equals 0.938, 3, or 6.255 A/g, depending on a chosen operational point. The sensitivity threshold in terms of photodiode dark current equals 107 × 10-9 g, 33.3 × 10-9 g, 16 × 10-9 g. The dynamic range for the photodiode equals ± 3.2 × 10-3 g, while for the measuring transducer it is ±0.32g, ±0.1, or ±0.05g. To decrease the noise down to 0.1 µ g, the inertial mass should amount at least to 65 × 10-7 kg, and the average laser noise power should be below 1 %. © 2022 IEEE.

关键词： Accelerometers

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Attitude Takeover control for Noncooperative Space Targets Based on Gaussian Processes with Online Model Learning

arXiv

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arXiv 2023年

作者： Liu, Yuhan Wang, Pengyu Lee, Chang-Hun Tóth, Roland The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Flight Dynamics and Control Laboratory Department of Aerospace Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of The Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

One major challenge for autonomous attitude takeover control for on-orbit servicing of spacecraft is that an accurate dynamic motion model of the combined vehicles is highly nonlinear, complex and often costly to identify online, which makes traditional model-based control impractical for this task. To address this issue, a recursive online sparse Gaussian Process (GP)-based learning strategy for attitude takeover control of noncooperative targets with maneuverability is proposed, where the unknown dynamics are online compensated based on the learnt GP model in a semi-feedforward manner. The method enables the continuous use of on-orbit data to successively improve the learnt model during online operation and has reduced computational load compared to standard GP regression. Next to the GP-based feedforward, a feedback controller is proposed that varies its gains based on the predicted model confidence, ensuring robustness of the overall scheme. Moreover, rigorous theoretical proofs of Lyapunov stability and boundedness guarantees of the proposed method-driven closed-loop system are provided in the probabilistic sense. A simulation study based on a high-fidelity simulator is used to show the effectiveness of the proposed strategy and demonstrate its high performance. © 2023, CC BY-NC-SA.

关键词： Maneuverability

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MARS: Multi-Agent Deep Reinforcement Learning for Real-Time Workflow Scheduling in Hybrid Clouds with Privacy Protection 30

MARS: Multi-Agent Deep Reinforcement Learning for Real-Time ...

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30th IEEE International Conference on Parallel and Distributed systems, ICPADS 2024

作者： Cheng, Long He, Haoyang Gu, Yan Liu, Qingzhi Zhao, Zhiming Fang, Fang North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources School of Control and Computer Engineering Beijing China Wageningen University and Research Information Technology Group Netherlands University of Amsterdam Research Group of Multi-Scale Networked Systems Netherlands

ISBN: (纸本)9798331515966

Scheduling workflows in hybrid cloud environments presents significant challenges due to the inherent complexity of workflows and the dynamic nature of cloud resources. This complexity is further increased when attempting to balance workflow performance with privacy protection. Recent efforts have leveraged deep reinforcement learning (DRL) to address these challenges. However, most of these approaches rely on single-agent models, which can lead to security issues and scalability problems due to their centralized processing. Specifically, the properties of workflows are transferred to the single agent, which risks leaking privacy information. Our paper addresses these issues by introducing MARS, a real-time workflow scheduling method that prioritizes privacy protection in hybrid clouds. MARS leverages multi-agent deep reinforcement learning (MADRL) to optimize the workflow scheduling of cloud virtual machines (VMs). The benefit of our solution is that it relies on the collaborative learning of multi-agents on multiple VMs, which could assign user data to specific cloud servers for privacy protection while sharing training experiences between agents. In our implementation, MARS aims to reduce workflow completion time and operational costs while complying with strict privacy protection guidelines. The experimental results demonstrate that MARS can significantly surpass existing methods, reducing makespan by an average of 53.18% and costs by 61.98% compared to basic techniques, and achieving 20.26% and 25.71% improvements over the latest advanced methods, respectively. © 2024 IEEE.

关键词： Deep reinforcement learning

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Optimal Synthesis of LTI Koopman Models for Nonlinear systems with Inputs

arXiv

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arXiv 2022年

作者： Iacob, Lucian Cristian Tóth, Roland Schoukens, Maarten Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

A popular technique used to obtain linear representations of nonlinear systems is the so-called Koopman approach, where the nonlinear dynamics are lifted to a (possibly infinite dimensional) linear space through nonlinear functions called observables. In the lifted space, the dynamics are linear and represented by a so-called Koopman operator. While the Koopman theory was originally introduced for autonomous systems, it has been widely used to derive linear time-invariant (LTI) models for nonlinear systems with inputs through various approximation schemes such as the extended dynamics mode decomposition (EDMD). However, recent extensions of the Koopman theory show that the lifting process for such systems results in a linear parameter-varying (LPV) model instead of an LTI form. As LTI Koopman model based control has been successfully used in practice and it is generally temping to use such LTI descriptions of nonlinear systems, due to the simplicity of the associated control tool chain, a systematic approach is needed to synthesise optimal LTI approximations of LPV Koopman models compared to the ad-hoc schemes such as EDMD, which is based on least-squares regression. In this work, we introduce optimal LTI Koopman approximations of exact Koopman models of nonlinear systems with inputs by using 2-gain and generalized H2 norm performance measures. We demonstrate the advantages of the proposed Koopman modelling procedure compared to EDMD. © 2022, CC BY-NC-SA.

关键词： Nonlinear systems

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Model-based epidemic data reconstruction using feedback linearization

Model-based epidemic data reconstruction using feedback line...

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2022 IEEE International Conference on Electrical, computer, and Energy Technologies, ICECET 2022

作者： Csutak, Balazs Polcz, Peter Szederkenyi, Gabor Pázmány Péter Catholic University Faculty of Information Technology and Bionics Budapest Hungary Institute for Computer Science and Control Systems and Control Laboratory Kende u. 13-17 BudapestH-1111 Hungary

ISBN: (数字)9781665470872

ISBN: (纸本)9781665470872

In this paper, a model-based method is proposed for the reconstruction of non-measured epidemic data of the COVID-19 pandemic in Hungary. Only the data series showing the daily number of hospitalized people are used for the reconstruction together with a nonlinear dynamical model of epidemic spread containing 8 compartments. The unknown input of the model is the infection rate, which is computed through the solution of a feedback linearization-based asymptotic output tracking problem, where the reference is the actually observed number of hospitalized people. Computations show good match with of hospitalized people. Computations show good match with previous reconstruction results, and show a roughly 3.5-4-fold underdetection of infections until the Omicron wave. © 2022 IEEE.

关键词： Feedback linearization

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Stability focused evaluation and tuning of special ground vehicle tracking algorithms

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IFAC-PapersOnLine 2023年第2期56卷 9282-9287页

作者： Peter Bauer Mihaly Nagy Gergely Istvan Kuna Adam Kisari Erno Simonyi Antal Hiba Istvan Drotar Research Center of Vehicle Industry Széchenyi István University Győr Hungary Systems and Control Laboratory Institute for Computer Science and Control ELKH Budapest Hungary Computational Optical Sensing and Processing Laboratory Institute for Computer Science and Control ELKH Budapest Hungary Széchenyi István University Győr Hungary

This paper deals with a special tracking problem when a ground vehicle should be tracked by a multicopter flying ahead of the vehicle. Pre-designed vehicle route is assumed and the UAV stops or slows down at every intersection to react to route changes. After introducing the problem, the methods applied in a real flight demonstration in the Smart City module of ZalaZONE proving ground are presented. Then new methods are introduced to possibly improve performance. The main focus of the article is the evaluation of the stability of the methods and the provision of tuning guidelines. All of the introduced methods is tuned based-on the guidelines considering real ground vehicle test data and the high fidelity simulation of the applied multicopter. The two best methods are compared in detail and guidelines of their applicability are provided.

关键词： vehicle tracking forerunner UAV stability velocity scaling control PD control freedrive routedrive

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Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case 63

Optimal Linear Deception Attacks on Remote State Estimation ...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Shang, Jun Zhang, Hanwen Zhou, Jing Chen, Tongwen Tongji University Shanghai Research Institute for Intelligent Autonomous Systems National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Department of Control Science and Engineering Shanghai200092 China University of Science and Technology Beijing Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering Beijing100083 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada

ISBN: (纸本)9798350316339

This study addresses linear attacks on remote state estimation within the context of a constrained alarm rate. Smart sensors, which are equipped with local Kalman filters, transmit innovations instead of raw measurements through a wireless communication network. This transmission is vulnerable to malicious data interception and manipulation by attackers. The aim of this research is to identify the optimal attack strategy that degrades the system performance while adhering to stealthiness constraints. A notable innovation of this paper is the direct association of the attack's stealthiness with the alarm rate, diverging from traditional approaches that rely on the covariance of the innovation or the Kullback-Leibler divergence, which are conventional metrics that have been extensively explored in previous studies. Our findings reveal that the optimal attack strategy exhibits some structural characteristics in systems of low dimensions. The performance of the proposed attack strategy is demonstrated through numerical examples. © 2024 IEEE.

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