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International Conference on Information Fusion

作者： Tianhao Zhang Shenglin Wang Nidhal Bouaynaya Radu Calinescu Lyudmila Mihaylova Automatic Control and Systems Engineering The University of Sheffield UK Department of Electrical and Computer Engineering Rowan University USA Department of Computer Science University of York UK

The superior performance of object detectors is often established under the condition that the test samples are in the same distribution as the training data. However, in many practical applications, out-of-distribution (OOD) instances are inevitable and usually lead to uncertainty in the results. In this paper, we propose a novel, intuitive, and scalable probabilistic object detection method for OOD detection. Unlike other uncertainty-modeling methods that either require huge computational costs to infer the weight distributions or rely on model training through synthetic outlier data, our method is able to distinguish between in-distribution (ID) data and OOD data via weight parameter sampling from proposed Gaussian distributions based on pre-trained networks. We demonstrate that our Bayesian object detector can achieve satisfactory OOD identification performance by reducing the FPR95 score by up to 8.19% and increasing the AUROC score by up to 13.94% when trained on BDD100k and VOC datasets as the ID datasets and evaluated on COCO2017 dataset as the OOD dataset.

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A novel approach for the prevention of ionizing radiation-induced bone loss using a designer multifunctional cerium oxide nanozyme

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Bioactive Materials 2023年第3期21卷 547-565页

作者： Fei Wei Craig J.Neal Tamil Selvan Sakthivel Yifei Fu Mahmoud Omer Amitava Adhikary Samuel Ward Khoa Minh Ta Samuel Moxon Marco Molinari Jackson Asiatico Michael Kinzel Sergey N.Yarmolenko Vee San Cheong Nina Orlovskaya Ranajay Ghosh Sudipta Seal Melanie Coathup Biionix Cluster Department of Internal MedicineCollege of MedicineUniversity of Central FloridaOrlandoFLUSA Advanced Materials Processing and Analysis Centre Nanoscience Technology Center(NSTC)Materials Science and EngineeringCollege of MedicineUniversity of Central FloridaOrlandoFLUSA CMC Materials 870 North CommonsDrAuroraILUSA Department of Chemistry Oakland UniversityRochesterMIMIUSA School of Applied Sciences Department of Chemical SciencesUniversity of HuddersfieldUK Department of Mechanical and Aerospace Engineering University of Central FloridaOrlandoFLUSA Engineering Research Center for Revolutionizing Biomaterials North Carolina A&T UniversityGreensboroNCUSA Department of Automatic Control and Systems Engineering Insigneo Institute for In Silico MedicineUniversity of SheffieldSheffieldS13JDUK

The disability,mortality and costs due to ionizing radiation(IR)-induced osteoporotic bone fractures are sub-stantial and no effective therapy *** radiation increases cellular oxidative damage,causing an imbalance in bone turnover that is primarily driven via heightened activity of the bone-resorbing *** demonstrate that rats exposed to sublethal levels of IR develop fragile,osteoporotic *** reactive surface sites,cerium ions have the ability to easily undergo redox cycling:drastically adjusting their electronic con-figurations and versatile catalytic *** properties make cerium oxide nanomaterials *** show that an engineered artificial nanozyme composed of cerium oxide,and designed to possess a higher fraction of trivalent(Ce^(3+))surface sites,mitigates the IR-induced loss in bone area,bone architecture,and *** investigations also demonstrate that our nanozyme furnishes several mechanistic avenues of protection and selectively targets highly damaging reactive oxygen species,protecting the rats against IR-induced DNA damage,cellular senescence,and elevated osteoclastic activity in vitro and in ***,we reveal that our nanozyme is a previously unreported key regulator of osteoclast formation derived from macrophages while also directly targeting bone progenitor cells,favoring new bone formation despite its exposure to harmful levels of IR in *** findings open a new approach for the specific prevention of IR-induced bone loss using synthesis-mediated designer multifunctional nanomaterials.

关键词： Ionizing radiation Osteoporosis Nanozyme Cerium oxide Bone strength Bone resorption

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Sublevel Set Approximation in The Hausdorff and Volume Metric with Application to Path Planning and Obstacle Avoidance

arXiv

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arXiv 2023年

作者： Jones, Morgan The Department of Automatic Control and Systems Engineering The University of Sheffield Amy Johnson Building Mappin Street SheffieldS1 3JD United Kingdom

Under what circumstances does the "closeness" of two functions imply the "closeness" of their respective sublevel sets? In this paper, we answer this question by showing that if a sequence of functions converges strictly from above/below to a function, V, in the L∞ (or L1) norm then these functions yield a sequence sublevel sets that converge to the sublevel set of V with respect to the Hausdorff metric (or volume metric). Based on these theoretical results we propose Sum-of-Squares (SOS) numerical schemes for the optimal outer/inner polynomial sublevel set approximation of various sets, including intersections and unions of semialgebraic sets, Minkowski sums, Pontryagin differences and discrete points. We present several numerical examples demonstrating the usefulness of our proposed algorithm including approximating sets of discrete points to solve machine learning one-class classification problems and approximating Minkowski sums to construct C-spaces for computing optimal collision-free paths for Dubin’s car. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Hybrid Deep Learning Model for Short-Term Wind Speed Forecasting Based on Time Series Decomposition and Gated Recurrent Unit

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Complex System Modeling and Simulation 2021年第4期1卷 308-321页

作者： Changtong Wang Zhaohua Liu Hualiang Wei Lei Chen Hongqiang Zhang School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China Department of Automatic Control and Systems Engineering the University of SheffieldSheffieldS13JDUK.

Accurate wind speed prediction has been becoming an indispensable technology in system security,wind energy utilization,and power grid dispatching in recent ***,it is an arduous task to predict wind speed due to its variable and random *** the objective to enhance the performance of forecasting short-term wind speed,this work puts forward a hybrid deep learning model mixing time series decomposition algorithm and gated recurrent unit(GRU).The time series decomposition algorithm combines the following two parts:(1)the complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN),and(2)wavelet packet decomposition(WPD).Firstly,the normalized wind speed time series(WSTS)are handled by CEEMDAN to gain pure fixed-frequency components and a residual *** WPD algorithm conducts the second-order decomposition to the first component that contains complex and high frequency signal of raw ***,GRU networks are established for all the relevant components of the signals,and the predicted wind speeds are obtained by superimposing the prediction of each *** from two case studies,adopting wind data from laboratory and wind farm,respectively,suggest that the related trend of the WSTS can be separated effectively by the proposed time series decomposition algorithm,and the accuracy of short-time wind speed prediction can be heightened significantly mixing the time series decomposition algorithm and GRU networks.

关键词： deep learning complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN) gated recurrent unit(GRU) short term wavelet packet decomposition wind speed prediction

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Feedback-Optimizing Model Predictive control for Constrained Linear systems

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IFAC-PapersOnLine 2021年第6期54卷 43-49页

作者： Amba Asuk Paul Trodden Department of Automatic Control and Systems Engineering University of Sheffield UK

This paper proposes a feedback-optimizing model predictive control (FOMPC) algorithm to regulate a disturbed linear time-invariant system to an equilibrium point that is the solution to a steady-state optimization problem. This regulation is achieved without knowledge of the optimal steady-state set-points or explicit solution of the steady-state optimization problem. We develop the FOMPC algorithm by indirectly formulating the residuals of the Karush–Kuhn– Tucker (KKT) optimality conditions associated with the steady-state optimization into the transient performance objective of the MPC controller. By solving the steady-state optimization problem implicitly, via feedback, the proposed algorithm allows the optimal steady-states to be reached despite unknown disturbances and/or set-point changes, and in the presence of linear inequality constraints. We establish recursive feasibility and stability of the approach, and show that FOMPC is a generalization of conventional tracking model predictive control.

关键词： Optimization Model Predictive control Tracking Path Following Predictive control Economic Predictive control

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Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI)∗

arXiv

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arXiv 2023年

作者： Machado, Gabriel F. Jones, Morgan Department of Automatic Control and Systems Engineering The University of Sheffield Amy Johnson Building Mappin Street SheffieldS1 3JD United Kingdom

Modern societies have an abundance of data yet good system models are rare. Unfortunately, many of the current system identification and machine learning techniques fail to generalize outside of the training set, producing models that violate basic physical laws. This work proposes a novel method for the Sparse Identification of Nonlinear Dynamics with Side Information (SINDy-SI). SINDy-SI is an iterative method that uses Sum-of-Squares (SOS) programming to learn optimally fitted models while guaranteeing that the learned model satisfies side information, such as symmetries and physical laws. Guided by the principle of Occam’s razor, that the simplest or most regularized best fitted model is typically the superior choice, during each iteration SINDy-SI prunes the basis functions associated with small coefficients, yielding a sparse dynamical model upon termination. Through several numerical experiments we will show how the combination of side information constraints and sparse polynomial representation cultivates dynamical models that obey known physical laws while displaying impressive generalized performance beyond the training set. Copyright © 2023, The Authors. All rights reserved.

关键词： Dynamics

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Accurate TCP Position and Orientation Trajectory Generation in 6DOF Robotic Manipulators and CNC Machine Tools using FIR Filtering and Haversine Synchronisation

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Procedia CIRP 2023年 120卷 27-32页

作者： Rob Ward Burak Sencer Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK Advanced Manufacturing Research Centre University of Sheffield Rotherham S60 5TZ UK Mechanical Engineering Department Oregon State University Corvallis OR USA

The use of robotics in manufacturing is rapidly growing. One promising application in particular is the use of robots as machining platforms. Robotic machining offers many advantages such as large operating envelopes, flexibility in operations and low installation and running costs. Robotic machining platforms much like computer numerically controlled (CNC) machine tools are commanded by numerical controllers (NCs) using the well established G-code part programming language (ISO-6983). Toolpaths are defined in the work piece coordinate system (WCS) as a series of discrete tool centre point (TCP) positions and tool orientations. The role of the NC is to generate smooth feed drive or robot joint commands such that the tool or end effector travels along the commanded toolpath whilst satisfying TCP position and orientation tolerances and robot/machine tool kinematic constraints. Interpolating tool orientations directly in the WCS requires complex real-time spherical interpolation computations. Overcoming this challenge, this paper introduces a C 4 continuous tool path trajectory generation method for 6DOF motion. The tool centre point position is smoothed in the WCS, however, the tool orientation is smoothed directly in the rotary coordinate system without the requirement for spherical interpolation. The interpolated tool orientation trajectory follows the path of the great circle arc using the modified Haversine method eliminating non-linear interpolation errors present in linear interpolation of rotary axis positions (machine coordinate system interpolation). The proposed method is validated by simulation of a 6DOF robotic manipulator.

关键词： Robotic Machining interpolation Trajectory Generation Pose control Motion control

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An Adaptive CUSUM Approach for Automating Sleep Apnoea Analysis Based on Pulse and Oximetry Data

An Adaptive CUSUM Approach for Automating Sleep Apnoea Analy...

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IEEE International Conference on Mechatronics and Automation

作者： Dongjin Yang Eishaan Bhargava Heather Elphick Lyudmila S. Mihaylova Dept. of Automatic Control and Systems Engineering University of Sheffield UK Department of Paediatric Otolaryngology Sheffield Children’s Hospital Sheffield UK Department of Paediatric Respiratory and Sleep Medicine Sheffield Children’s Hospital Sheffield UK

Sleep apnoea is a common sleep disorder during human sleep. It is usually diagnosed by a doctor after recording one nights’ sleep signals. Patients have to go to the hospital to record sleep signals, which is time-consuming and resource-intensive. The study focused on two signals, pulse data and oximetry data, with the aim of detecting apnoea using a single signal. This paper introduced an anomaly detection approach using the adaptive cumulative sum (ACUSUM) change point detection algorithm to monitor outliers in the signal. In addition, the test results of ACUSUM will be compared with the test results of classical CUSUM. Besides, the threshold selection has been changed from an unchanging constant to a value related to the standard deviation of the selected signal based on a rational subgroup process. The results of the comparison confirm that ACUSUM is better than classical CUSUM in the accuracy of automatic detection.

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Numerical Comparison of Collocation vs Quadrature Penalty Methods

Numerical Comparison of Collocation vs Quadrature Penalty Me...

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IEEE Conference on Decision and control

作者： Martin P. Neuenhofen Eric C. Kerrigan Yuanbo Nie Department of Electrical & Electronic Engineering Imperial College London London UK Department of Electrical & Electronic Engineering and Department of Aeronautics Imperial College London London UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK

Direct transcription with collocation-type methods (CTM) is a popular approach for solving dynamic optimization problems. It is known that these types of methods can fail to converge for problems that feature singular-arc solutions, high-index differential-algebraic equations and overdetermined constraints. Recently, we proposed the use of quadrature penalty methods (QPM) as an alternative numerical approach to collocation-type methods. In contrast to the concept of collocation, which requires constraint-residuals to equal zero at individual points (e.g. at collocation points), the main idea of QPM is to simply oversample this number of points and use their respective quadrature weights in a quadratic penalty term, coining the name of quadrature penalty. In this paper, we provide numerical case studies and a broad numerical comparison on a wide range of problems, highlighting the benefits of QPM over CTM not only in difficult problems, but also in solving problems competitively to CTM. These results show that QPM can be considered an attractive first go-to method when solving general dynamic optimization problems.

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Robust Distributed control for DC Microgrids with System Constraints

Robust Distributed Control for DC Microgrids with System Con...

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Mediterranean Conference on control and Automation (MED)

作者： Grigoris Michos Pablo R. Baldivieso-Monasterios George C. Konstantopoulos Department of Automatic Control &amp Systems Engineering University of Sheffield Sheffield UK Department of Electrical and Computer Engineering University of Patras Rion Greece

ISBN: (数字)9781665406734

ISBN: (纸本)9781665406741

This work proposes a distributed robust control architecture for meshed DC Microgrid networks. Each interlinking converter is modelled as a network node and is connected in parallel to a constant power load representing the network’s power consumption. Each node employs a local controller consisting of two parts; current regulation based on a modified version of the state-limiting PI and a distributed MPC driving the system to desired setpoints. We analytically prove each controller’s robustness to model variations caused by changes in both the power demand and the transmitted information among the subsystems. The concept of positive invariance sets and the inherent robustness properties of the nominal MPC are used to prove recursive feasibility of the optimal control problem and guarantee constraint satisfaction at all times. The stability proof of the cascaded node dynamics is based upon the emerging properties of both the state limiting PI and the distributed MPC design. Demonstration of the results is given in a simulated scenario.

关键词： Current control Uncertain systems Power demand Decentralized control Microgrids Robustness Stability analysis

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