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检索条件"机构=Department of Automatic Control and Systems Engineering University of Sheffield"

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Learning Input Driven Dynamic Bayesian Networks with Measurement Noise 23

Learning Input Driven Dynamic Bayesian Networks with Measure...

引用

23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Veres, David Li, Ping Kadirkamanathan, Visakan The University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350374889

Dynamic Bayesian Networks (DBNs) are useful tools for modelling complex systems whose network representations can be elicited a priori or learnt from data. In this paper, a maximum likelihood Doubly-Iterative Expectation Maximization (DI-EM) Algorithm is developed for the identification of grey-box ARMAX state-space model representations of DBNs involving known, noisy measurement processes. The grey-box model incorporates network dependencies among time series variables and exploits time series data of low longitudinal and high cross-sectional dimensions. A network learning procedure is developed using a score-based structure-selection method to find the underlying network of an input-driven dynamical system. By computing a finite data version of the Bayesian Information Criterion (BIC) for small sample sizes, the proposed method's performance is investigated on simulated and real-world data. The algorithm recovers the underlying ground-truth networks of simulated systems under finite data criteria with Jaccard Coefficient values of up to 0.84, and selects structures with improved weighted mean-squared error loss over a baseline black-box model fit on real-world data. © 2024 IEEE.

关键词： Expectation maximization algorithm

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A Power-Communication Co-Simulation Platform for Real-Time Microgrid Cyber Security Analysis

A Power-Communication Co-Simulation Platform for Real-Time M...

引用

2024 International Conference on Artificial Intelligence of Things and systems, AIoTSys 2024

作者： Qiu, Dongmeng Liu, Mengxiang Zhang, Xin University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798331507886

The rapid digitalisation process in power system has greatly benefited the large-scale integration of distributed energy resources (DERs), essentially accelerating the progress towards net zero. However, numerous cyber attacks such as false data injection (FDI) attacks are impeding the normal control and operation activities. This paper aims to establish a real-Time microgrid co-simulation platform to fully study the impacts of realistic attack events on micorgrid's control performance. Although there exist a large number of power-communication co-simulation platforms for the power system, they are designed to mainly provide validation services for control and operation algorithms and little attention has been paid to the cyber security. In the established microgrid platform, power and communication parts are simulated in Typhoon Hardware-in-The-loop(HIL) 602+ and EXata Network Simulator, respectively, and a dedicated synchronisation scheme is developed and embedded in Raspberry Pis to achieve master-slave data exchange between them. Based on the advanced cyber libraries provided by EXata, realistic FDI and packet drop attacks are mounted against the mapped communication links within EXata. The results indicate that these cyber attacks can severely influence the microgrid control performance including destabilising system states and specific state deviations, further demonstrating the necessity of deploying effective cyber-resilience enhancement mechanisms. © 2024 IEEE.

关键词： Cyber attacks

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Optimized Spatial Filter Selection for Transfer Learning in Brain-Computer Interface 3

Optimized Spatial Filter Selection for Transfer Learning in ...

引用

3rd IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2024

作者： A A Mohamed, Mohamed Giles, Joshua Arvaneh, Mahnaz University of Sheffield Automatic control and Systems Engineering Department Sheffield United Kingdom

ISBN: (纸本)9798350378009

The Common Spatial Patterns (CSP) algorithm has shown great efficacy in extracting features for Brain-Computer Interfaces (BCIs), particularly in motor imagery BCIs. However, CSP performs poorly when dealing with limited labeled data, which leads to long calibration time at the beginning of each session. To overcome this challenge, we leverage source data, i.e., labeled data from other subjects, to transfer knowledge across subjects. This work proposes a novel approach termed Scaled and Warped CSP-based Transfer Learning (SW-CSP-TL). This method aligns source data with the temporal and amplitude structure of target data before computing CSP filters, ensuring optimization for capturing discriminative features relevant to the target domain. We evaluate the proposed SW-CSP-TL algorithm using the publicly available dataset 2a from BCI Competition IV and compare its performance with that of the classical CSP algorithm and the transfer learning CSP algorithm (CSP-TL) without amplitude scaling and temporal warping. Our algorithm exhibits superior performance particularly when the training data size is relatively small. Results demonstrate that for 5 and 15 training trials per class from the target session, SW-CSP-TL outperformed the classical CSP by an average of 10%, and 8%, respectively. © 2024 IEEE.

关键词： Transfer learning

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A Lightweight Target Following Architecture for Indoor Mobile Robot 25

A Lightweight Target Following Architecture for Indoor Mobil...

引用

25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Wang, Fuli Hutabarat, Windo Tiwari, Ashutosh The University Of Sheffield Department Of Automatic Control And Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340266

Manufacturing efficiency and transport operations are being significantly improved by mobile robots. As the implementation of a configurable, lightweight, and stateof-the-art robotic system is required for current manufacturing sectors to maximize the use of mobile robots, this paper presents a software architecture comprised of perception and action systems for human following in real time. The perception system uses the YOLOv8 computer vision model to identify and estimate human pose. Additionally, an algorithm is developed using the 3D information from a stereo camera to determine which target and whether to follow. Once the perception system perceives the desired target information, the action system can control and coordinate the robot using the ROS. Experimental results from the physical robot demonstrate the feasibility of the system architecture. © 2024 IEEE.

关键词： Mobile robots

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A low voltage ride through (LVRT) strategy using an active superconductor fault current limiter (SFCL) for a virtual synchronous generator (VSG) connected to a weak grid

A low voltage ride through (LVRT) strategy using an active s...

引用

2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Kisinga, Daniel Angelo Trodden, Paul Department of Automatic Control and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9798350396782

A function of grid-connected VSGs is facilitating the recovery of sagging voltages to nominal levels, achieved by supplying reactive power (Q) to the grid. During normal operation, however, a VSG is required to supply active power (P) at unity power factor and, therefore, in order to supply the Q required in the event of a sagging voltage, the VSG must change its control mode from P-supply to PQ- or Q-supply. Such transitions may induce high current flows—caused by the sudden reduction of the voltage during the sag—which are potentially damaging to the power semiconductor devices of the VSG;if these effects are to be avoided, the supplied current must be limited to its rated value, but this may result in a low power transfer from the VSG to the grid. To circumvent these problems, in this paper we propose a LVRT strategy using an active SFCL. We show that the proposed strategy, which combines a PQ decoupling scheme with an active SFCL, ensures maximum power transfer with an improved transient response during LVRT. © 2023 IEEE.

关键词： active SFCL LVRT PQ control voltage sag VSG

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Reinforcement Learning for Multiple-Input Multiple-Output control in Metal Additive Manufacturing 20

Reinforcement Learning for Multiple-Input Multiple-Output Co...

引用

20th IEEE International Conference on Networking, Sensing and control, ICNSC 2023

作者： Grais, Emad M. Notley, Scott V. Panoutsos, George University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350369502

In laser powder bed fusion additive manufacturing, using fixed values for the process parameters (beam power, velocity, and other parameters) may not lead to homogeneously distributed heat in all locations in the build, especially around complex design features. This could lead to builds with defects, leading to poor mechanical and micro-structure properties. To guarantee heat homogeneity, the process parameters need to be actively controlled to adapt to different locations in the build. Builds with varying geometrical features would need different control strategies. In this work, we propose to use reinforcement learning (RL) to control, for the first time, simultaneously multiple AM process parameters to achieve consistent melting properties. Our results show that using RL as a multiple-input multiple-output control system achieves a more consistent meltpool geometry. © 2023 IEEE.

关键词： Reinforcement learning

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On Sparse Nonlinear System Identification Using Orthogonal Matching Pursuit, Orthogonal Least Squares and LASSO 32

On Sparse Nonlinear System Identification Using Orthogonal M...

引用

32nd Mediterranean Conference on control and Automation, MED 2024

作者： Wei, Hua-Liang The University of Sheffield The Department of Automatic Control and Systems Engineering SheffieldSI 3JD United Kingdom

ISBN: (纸本)9798350395440

System identification, as a rich and vital discipline, provides a practical and general methodology and tool for quantitatively modelling the input-output relationships of dynamical systems. Sparse nonlinear system identification (SNSI), especially parametric sparse nonlinear system identification (PSNSI), is an important and vital field of research with a wide range of applications. This work is concerned with PSNSI and particular attention is paid to the assessment of three well-known mainstream sparse learning methods, namely, orthogonal least squares (OLS), orthogonal matching pursuit (OMP) and least absolute shrinkage and selection operator (LASSO). The performances of these methods are tested and evaluated through three case studies relating to PSNSI problems. The research results and findings of this work provide practical useful information and guidance for researchers to better choose or adapt methods when solving PSNSI problems. © 2024 IEEE.

关键词： Dynamical systems

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Robotic Assembly of Aviation Fuel Probes and Parameters Optimisation Using Bees Algorithm 25

Robotic Assembly of Aviation Fuel Probes and Parameters Opti...

引用

25th IEEE International Conference on Industrial Technology, ICIT 2024

作者： Lin, Xiaoguo Qu, Mo Noguera, Marc Auledas Tiwari, Ashutosh Wang, Yongjing University Of Birmingham Department Of Mechanical Engineering Birmingham United Kingdom University Of Sheffield Department Of Automatic Control And Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350340266

Robots for automated assembly are being progressively implemented in the aerospace manufacturing sector. The dim and complex internal structure of the aircrafts significantly complicates the operation of robotic arms through visual system. This paper proposes an assembly strategy based on force-feedback control for fuel probe installation inside the aircraft wings, enabling autonomous assembly of tubular objects under translational and rotational misalignments. Furthermore, the Bees Algorithm (BA) is employed in a simulation environment to optimise the parameters of this control strategy. The results demonstrate that BA can effectively decrease the overall installation time while simultaneously proving the effectiveness of this method and its potential applicability in aerospace manufacturing. © 2024 IEEE.

关键词： Probes

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Improving Common Spatial Patterns in Brain-Computer Interface Using Dynamic Time Warping and EEG Normalization 2

Improving Common Spatial Patterns in Brain-Computer Interfac...

引用

2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Mohamed, Mohamed A.A. Mansour, Salem Soulatiantork, Payam Ang, Kai Keng Soon, Phua Kok Arvaneh, Mahnaz University of Sheffield Automatic Control and Systems Engineering Department Sheffield United Kingdom Singapore

ISBN: (纸本)9798350300802

Common spatial patterns (CSP) is widely employed for spatial filtering and feature extraction in electroencephalogram (EEG)-based brain-computer interfaces (BCIs), However, the non-stationary nature of EEG signals can lead to poor estimation of CSP. To address this drawback, this paper proposes a novel algorithm called scaled and warped CSP (SW-CSP). The proposed algorithm enhances the classical CSP by reducing within EEG class non-stationarity across both time and amplitude domains, followed by automatically selecting the most discriminative features. First, the maximum-minimum scaling is applied to align amplitude of each EEG trial to its class average. Next, dynamic time warping (DTW) temporally aligns each scaled EEG trial to its class average. Thereafter, the scaled and warped EEG trials are used to compute the CSP covariance matrices. Finally, the proposed Fisher's score is used to select most discriminative SW-CSP filters. The proposed SW-CSP algorithm is evaluated using two datasets, and compared with the CSP algorithm and the previously proposed DTW-CSP. The results showed that the SW-CSP significantly outperformed both CSP and DTW-CSP (p © 2023 IEEE.

关键词： brain-computer interface common spatial patterns dynamic time warping EEG Fisher's score non-stationarity

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Developing a Novel MATLAB control Toolbox for Encouraging Student Engagement 6

Developing a Novel MATLAB Control Toolbox for Encouraging St...

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6th Experiment at International Conference, exp.at 2023

作者： Rossiter, John Anthony University of Sheffield Department of Automatic Control and Systems Engineering United Kingdom

ISBN: (纸本)9798350314403

The numerous toolboxes within MATLAB [12] to aid student engagement and learning largely require deep understanding of coding, as well as the associated engineering. This paper discusses some work in progress which is focussing on developing files and resources for a control 101 course [17] which are both engaging and also have much lower pedestals of understanding before use. The intention is focus on attracting student interest and communicating core concepts before students need to begin the longer process of deep learning. Thus this toolbox fills a large gap in the current provision. © 2023 IEEE.

关键词： Students

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