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Intelligent obstacle avoidance algorithm for safe urban monitoring with autonomous mobile drones

Journal of Electronic Science and Technology 2024年第4期22卷 19-36页

作者： Didar Yedilkhan Abzal E.Kyzyrkanov Zarina A.Kutpanova Shadi Aljawarneh Sabyrzhan K.Atanov Department of Computer Engineering Astana IT UniversityAstana010000Kazakhstan Department of Computer and Software Engineering L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Automation and Control Systems L.N.Gumilyov Eurasian National UniversityAstana010000Kazakhstan Department of Software Engineering Jordan University of Science and TechnologyIrbid22110Jordan

The growing field of urban monitoring has increasingly recognized the potential of utilizing autonomous technologies,particularly in drone *** deployment of intelligent drone swarms offers promising solutions for enhancing the efficiency and scope of urban condition *** this context,this paper introduces an innovative algorithm designed to navigate a swarm of drones through urban landscapes for monitoring *** primary challenge addressed by the algorithm is coordinating drone movements from one location to another while circumventing obstacles,such as *** algorithm incorporates three key components to optimize the obstacle detection,navigation,and energy efficiency within a drone ***,the algorithm utilizes a method to calculate the position of a virtual leader,acting as a navigational beacon to influence the overall direction of the ***,the algorithm identifies observers within the swarm based on the current *** further refine obstacle avoidance,the third component involves the calculation of angular velocity using fuzzy *** approach considers the proximity of detected obstacles through operational rangefinders and the target’s location,allowing for a nuanced and adaptable computation of angular *** integration of fuzzy logic enables the drone swarm to adapt to diverse urban conditions dynamically,ensuring practical obstacle *** proposed algorithm demonstrates enhanced performance in the obstacle detection and navigation accuracy through comprehensive *** results suggest that the intelligent obstacle avoidance algorithm holds promise for the safe and efficient deployment of autonomous mobile drones in urban monitoring applications.

关键词： Drone swarms Fuzzy logic Intelligent solution Smart city Urban monitoring

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IMM-Based PMBM Filter for Maneuvering Extended Target Tracking

IMM-Based PMBM Filter for Maneuvering Extended Target Tracki...

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2024 Sensor Data Fusion: Trends, Solutions, Applications, SDF 2024

作者： Gu, Jiayi Shi, Jiaqi Shi, Kun Yang, Chaoqun Cao, Xianghui School of Automation Southeast University Nanjing China School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9798331527440

In the real-world scenarios of maneuvering extended target tracking (METT), targets always exhibit complex motion patterns, making it challenging for traditional tracking methods with single motion model to accurately capture their trajectories. To address this challenge, this paper proposes an interacting multiple model (IMM) based Poisson multi-Bernoulli mixture (PMBM) filter to track maneuvering extended targets. In this paper, we first introduce the basic model of the maneuvering extended targets. Then, we present the proposed IMM-based PMBM filter in detail. Finally, simulation experiments are conducted, which demonstrate the superior performance of the proposed filter in the term of tracking multiple maneuvering extended targets. © 2024 IEEE.

关键词： interacting multiple model maneuvering extended target tracking Poisson multi-Bernoulli mixture filter

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A Data-Based Feedback Relearning Algorithm for Uncertain Nonlinear Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1288-1303页

作者： Chaoxu Mu Yong Zhang Guangbin Cai Ruijun Liu Changyin Sun the School of Electrical and Information Engineering Tianjin UniversityTianjin 300072China the College of Missile Engineering Rocket Force University of EngineeringXi’an 710025China the School of Computer and Information Engineering Beijing Technology and Business UniversityBeijing 100048China the School of Automation Southeast UniversityNanjing 210096China

In this paper,a data-based feedback relearning algorithm is proposed for the robust control problem of uncertain nonlinear *** by the classical on-policy and off-policy algorithms of reinforcement learning,the online feedback relearning(FR)algorithm is developed where the collected data includes the influence of disturbance *** FR algorithm has better adaptability to environmental changes(such as the control channel disturbances)compared with the off-policy algorithm,and has higher computational efficiency and better convergence performance compared with the on-policy *** processing based on experience replay technology is used for great data efficiency and convergence *** experiments are presented to illustrate convergence stability,optimality and algorithmic performance of FR algorithm by comparison.

关键词： Data episodes experience replay neural networks reinforcement learning(RL) uncertain systems

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Towards migration from IEC 61131-3 to IEC 61499 in process industry: Redesign of visualisation 32

Towards migration from IEC 61131-3 to IEC 61499 in process i...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Kothalawala, Hiruni Jhunjhunwala, Pranay Vyatkin, Valeriy Aalto University Department of Electrical Engineering and Automation Espoo Finland Lulea Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden

ISBN: (纸本)9798350399714

This work focuses on reengineering an HMI implemented in a third-party legacy tool to an IEC 61499 implementation. We propose a method to re-engineer the view for a process system and gather relevant information for the migration of the controller to IEC 6499. The proposed methodology has been tested and demonstrated using a lab-scale 'Water process system' that is currently controlled using an IEC 61131-3 compliant PLC with a view and HMI developed on a legacy tool. It is intended to migrate to the IEC 61499-compliant EcoStruxure automation Expert (EAE) tool. © 2023 IEEE.

关键词： Process control

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Federated TD Learning in Heterogeneous Environments with Average Rewards: A Two-timescale Approach with Polyak-Ruppert Averaging 63

Federated TD Learning in Heterogeneous Environments with Ave...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Naskar, Ankur Thoppe, Gugan Koochakzadeh, Abbasali Gupta, Vijay Indian Institute of Science Dept. of Computer Science and Automation Bengaluru India Purdue University Dept. of Electrical and Computer Engineering IN United States

ISBN: (纸本)9798350316339

Federated Reinforcement Learning (FRL) provides a promising way to speedup training in reinforcement learning using multiple edge devices that can operate in parallel. Recently, it has been shown that even when these edge devices have access to different dynamic models, an optimal convergence rate that has a linear speedup proportional to the number of devices is achievable. However, this result requires that the stepsize in the algorithm be chosen in a manner dependent on the unknown model parameters. Also, it applies only to a discounted setting, which has been argued to fit episodic tasks better than continuing control tasks. In this paper, we obtain finite-time bounds for heterogeneous FRL with average rewards. We show that the optimal convergence rate with a linear speedup is possible even with a universal stepsize choice, independent of the underlying dynamics. To achieve our result, we modify the existing one-timescale FRL method to a novel two-timescale variant that additionally incorporates iterate averaging. © 2024 IEEE.

关键词： Federated learning

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Developing a Test Suite for Evaluating IEC 61499 Application Portability 32

Developing a Test Suite for Evaluating IEC 61499 Application...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Xavier, Midhun Laikh, Tatiana Patil, Sandeep Vyatkin, Valeriy Lulea Tekniska Universitet Computer and Space Engineering Department of Computer Science Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350399714

This paper presents the creation of a series of function blocks with the specific aim of testing the portability of IEC 61499 applications across diverse development and runtime environments. These function blocks have been developed to cover a wide range of test scenarios, including basic data types, functions, boundary conditions, and adapter features. The function blocks can be conveniently exported or imported through the use of XML files, thus facilitating seamless testing. By testing the runtime environment of different IEC 61499 systems, these function blocks help to identify and highlight any possible issues that may arise related to portability. © 2023 IEEE.

关键词： IEC 61499 Industrial Control System Portability Testing

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Methods of data streaming from IEC 61499 applications to Cloud storages 32

Methods of data streaming from IEC 61499 applications to Clo...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Lyu, Tuojian Galkin, Nikolai Liakh, Tatiana Yang, Chen-Wei Vyatkin, Valeriy Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleå Tekniska Universitet Computer and Space Engineering Department of Computer Science Sweden

ISBN: (纸本)9798350399714

This paper presents and discusses two methods for collecting data from decentralised control applications designed in IEC 61499 architecture. The topic is justified by the growing use of Cloud-based storage and presentation services in the Internet-of-Things systems. Enabling IEC 61499 devices with the capabilities of storing data in the Cloud and using web-based data presentation and data analytics is of great practical importance. Moreover, what is the most elegant way to configure such data streaming in IEC 61499 is an open question, to solving which this paper aims to provide state-of-the-art information. © 2023 IEEE.

关键词： Data Analytics

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Frequency-enhanced and decomposed transformer for multivariate time series anomaly detection

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Applied Intelligence 2025年第6期55卷 1-18页

作者： Li, Shijiang Wang, Zhihai Wang, Xiaokang Yin, Zihao Yao, Muyun School of Computer Science and Technology Beijing Jiaotong University Beijing China School of Automation and Intelligence Beijing Jiaotong University Beijing China Engineering Center on Computer Network Management in Hi-Speed Railway Ministry of Education Beijing Jiaotong University Beijing China

With the widespread adoption of the Internet of Things (IoT), vast amounts of multivariate time series data are generated, which reflect the operational status of systems. Accurate and efficient anomaly detection in these data is crucial for maintaining system stability. However, data from unstable environments often exhibit high volatility, data drift, and complex patterns of anomalies. Unsupervised anomaly detection models are typically designed for stable data and lack generalizability, leading to a high rate of false positives when applied to unstable data. This paper introduces the frequency-enhanced and decomposed transformer for anomaly detection (FDTAD), which is a novel anomaly detection model based on a transformer that is enhanced with frequency and time series decomposition. FDTAD addresses data drift by decomposing time series and leverages both time-domain and frequency-domain information to improve the generalization ability of the model. The model preserves major amplitudes in the frequency domain to extract primary periodic patterns, uses spectral residuals to capture detailed variations, and incorporates a frequency-domain correlation attention mechanism to extract dependencies in frequency-domain data in a sparse representation. Additionally, a spatiotemporal module is designed to extract the temporal correlations in the data and spatial correlations among the data with different attributes. FDTAD combines a data periodic pattern reconstructor and a data detailed pattern reconstructor through an adversarial mechanism to achieve maximum accuracy in reconstructing normal data. Extensive experiments on 10 public datasets demonstrate that FDTAD outperforms state-of-the-art baseline methods, with a 4.1% improvement in the F1 score and a 4.7% improvement in precision. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Time series

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Towards Interoperability of Edge Datacentre in the Energy Community with IEC 61850 Modelling 49

Towards Interoperability of Edge Datacentre in the Energy Co...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Yang, Chen-Wei Galkin, Nikolai Vyatkin, Valeriy Luleå Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350331820

Green modular datacentres are a new class of datacentres which can reduce the carbon footprints of the datacentre industry which accounts for close to 1% of total energy use worldwide. Green modular datacentres can operate as a prosumer and contribute energy to the energy grid through participation in the energy market as a part of the energy community. This paper investigates the interoperability of the datacentre in the energy community by proposing an IEC 61850 Logical Device model for a green modular datacentre. The applicability of the datacentre model is demonstrated through the re-implementation of the Energy Management System of an edge datacentre installation with the proposed IEC 61850 Logical Device model and its logical implementation in IEC 61499. © 2023 IEEE.

关键词： Interoperability

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Debugging approach for IEC 61499 control applications in FBME 32

Debugging approach for IEC 61499 control applications in FBM...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Akifev, Daniil Liakh, Tatiana Ovsiannikova, Polina Sorokin, Radimir Vyatkin, Valeriy Lulea Tekniska Universitet Department of Computer Science Computer and Space Engineering Sweden Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350399714

With the increase in the use of distributed control systems in industrial automation, it is becoming more challenging to analyze the behavior of the system to evaluate its quality. The lack of data coming from the system during operation also complicates debugging and error finding in the system software. The paper presents a quality control method of IEC 61499 industrial control software. The proposed method is based on a combination of several techniques: monitoring of the system behavior, recovering missing data with a simulator, and explanation of the recovered traces by highlighting a sequence of events that led to the explored state of the system. The paper integrates the method into modular IDE for IEC 61499 applications FBME. We also demonstrate the method on a simple example. © 2023 IEEE.

关键词： Quality control

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