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International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Rafał Bieszczad Adam Piłat Department of Automatic Control and Robotics Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering AGH University of Science and Technology Cracow Poland

This article presents the problem of designing a nonlinear observer for an active magnetic suspension system. The design process of the nonlinear Luenberger observer (also known as the Kazantzis-Kravaris-Luenberger observer) is discussed. Particular attention was paid to the main nonlinearity of the system - the electromagnetic force, which was modeled applying the function describing the change in inductance as a function of the distance of the levitating object from the electromagnet surface. Theoretical analyses were confirmed by the results of experimental studies in which the task of moving the sphere between the given positions using current control was carried out. control tasks were conducted in the real-time regime on an embedded platform. The measured signals and estimated velocity were analyzed in the context of future implementations in control applications.

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State-Space Piece-Wise Affine System Identification with Online Deterministic Annealing

State-Space Piece-Wise Affine System Identification with Onl...

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European control Conference (ECC)

作者： Christos N. Mavridis Aris Kanellopoulos John S. Baras Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Department of Electrical and Computer Engineering and the Institute for Systems Research University of Maryland College Park USA

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

We propose an online identification scheme for discrete-time piece-wise affine state-space models based on a system of adaptive algorithms running in two timescales. A stochastic approximation algorithm implements an online deterministic annealing scheme at a slow timescale, estimating the partition of the augmented state-input space that defines the switching signal. At the same time, an adaptive identification algorithm, running at a higher timescale, updates the parameters of the local models based on the estimate of the switching signal. Identifiability conditions for the switched system are discussed and convergence results are given based on the theory of two-timescale stochastic approximation. In contrast to standard identification algorithms for piece-wise affine systems, the proposed approach progressively estimates the number of modes needed and is appropriate for online system identification using sequential data acquisition. This progressive nature of the algorithm improves computational efficiency and provides real-time control over the performance-complexity trade-off, desired in practical applications. Experimental results validate the efficacy of the proposed methodology.

关键词： Switched systems Annealing Stochastic processes Switches Approximation algorithms Real-time systems System identification

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Trustworthy AI in Video Surveillance: The IMMAGINA Project

Trustworthy AI in Video Surveillance: The IMMAGINA Project

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2023 Italia Intelligenza Artificiale - Thematic Workshops, Ital-IA 2023

作者： Ledda, Emanuele Putzu, Lorenzo Delussu, Rita Fumera, Giorgio Roli, Fabio Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome00185 Italy Department of Informatics Bioengineering Robotics and Systems Engineering University of Genova Via Dodecaneso 35 Genova16146 Italy Department of Electric and Electronic Engineering University of Cagliari Via Marengo 3 Cagliari09100 Italy

The increasing adoption of machine learning and deep learning models in critical applications raises the issue of ensuring their trustworthiness, which can be addressed by quantifying the uncertainty of their predictions. However, the black-box nature of many such models allows only to quantify uncertainty through ad hoc superstructures, which require to develop and train a model in an uncertainty-aware fashion. However, for applications where previously trained models are already in operation, it would be interesting to develop uncertainty quantification approaches acting as lightweight "plug-ins" that can be applied on top of such models without modifying and re-training them. In this contribution we present a research activity of the Pattern Recognition and Applications Lab of the University of Cagliari related to a recently proposed post hoc uncertainty quantification method, we named dropout injection, which is a variant of the well-known Monte Carlo dropout, and does not require any re-training nor any further gradient descent-based optimization;this makes it a promising, lightweight solution for integrating uncertainty quantification on any already-trained neural network. We are investigating a theoretically grounded solution to make dropout injection as effective as Monte Carlo dropout through a suitable rescaling of its uncertainty measure;we are also evaluating its effectiveness in the computer vision tasks of crowd counting and density estimation for intelligent video surveillance, thanks to our participation in a project funded by the European Space Agency. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Pattern recognition

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Multiplier analysis of Lurye systems with power signals 63

Multiplier analysis of Lurye systems with power signals

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Heath, William P. Carrasco, Joaquin Bangor University School of Computer Science and Engineering Dean St LL57 1UT United Kingdom Nancy Rothwell Building University of Manchester Control Systems and Robotics Group Department of Electrical and Electronic Engineering M13 9PL United Kingdom

ISBN: (纸本)9798350316339

Multipliers can be used to guarantee both the Lyapunov stability and input-output stability of Lurye systems with time-invariant memoryless slope-restricted nonlinearities. If a dynamic multiplier is used there is no guarantee the closedloop system has finite incremental gain. It has been suggested in the literature that without this guarantee such a system may be critically sensitive to time-varying exogenous signals including noise. We show that multipliers guarantee the power gain of the system to be bounded and quantifiable. Furthermore power may be measured about an appropriate steady state bias term, provided the multiplier does not require the nonlinearity to be odd. Hence dynamic multipliers can be used to guarantee Lurye systems have low sensitivity to noise, provided other exogenous systems have constant steady state. We illustrate the analysis with an example where the exogenous signal is a power signal with non-zero mean. © 2024 IEEE.

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Ranking of attributes-comparative study based on data from stylometric domain 26

Ranking of attributes-comparative study based on data from s...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering systems, KES 2022

作者： Zielosko, Beata Stanczyk, Urszula Zabinski, Krzysztof Institute of Computer Science University of Silesia in Katowice B edzinska 39 Sosnowiec41-200 Poland Department of Graphics Computer Vision and Digital Systems Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 2A Gliwice44-100 Poland

The area of feature selection methods constantly expands along with the development of artificial intelligence domain, and has great impact on almost every field, whenever data is processed and explored. The paper presents research where a ranking method was proposed, inspired by an approach which comes from an algorithm for induction of decision rules. The ranking procedure was based on calculation of standard deviation for attributes, taking into account assigned class labels. This method was compared with another ranking mechanism, a modified version of popular Relief algorithm, with incorporating characteristics of variables by supervised discretisation. Comparison of obtained results included the aspect of knowledge representation as well as the perspective of the accuracy for constructed rule-based classifiers. The experiments were performed on datasets from stylometry domain, where authorship attribution was considered as a classification task, and stylometric descriptors as characteristic features defining writing styles of authors. © 2022 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://***/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 26th International Conference on Knowledge-Based and Intelligent Information & engineering systems (KES 2022)

关键词： Knowledge representation

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Robotic Assisted Immersive Therapy System for Stroke Rehabilitation

Robotic Assisted Immersive Therapy System for Stroke Rehabil...

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E-Health and Bioengineering Conference (EHB)

作者： Robert Gabriel Lupu Adrian Burlacu Ovidiu Catarama Ionut Sopot Department of Computer Engineering Gheorghe Asachi Technical University of Iasi Iasi Romania Department of Automatic Control and Applied Informatics Gheorghe Asachi Technical University of Iasi Iasi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

The number of stroke cases has increased dramatically in the last 30 years, and more and more people are left disabled because of stroke. It is vital to continue researching new ways to recover and improve their condition. Rehabilitation therapies are based on intensive and repeated training starting as soon as possible. However, the number of therapists is too few to treat the growing number of stroke survivors. Advanced technologies such as virtual reality (VR) and robot-assisted therapies have been introduced to improve stroke rehabilitation. VR-based rehabilitation immerses patients in simulated environments, providing visual feedback miming real-world activities. This approach motivates patients through interactive tasks while engaging their cognitive processes, which is crucial for neuroplasticity and motor recovery. Robot-assisted therapy complements VR by providing precise, repetitive movements and proprioceptive feedback. This paper presents a virtual reality- based and robotic-assisted upper limb neuromotor recovery system. The system combines VR immersion with robotic assistance, allowing patients to receive real-time guidance and support during exercise. The system adapts to the patient's condition, providing personalized visual and physical feedback to help relearn motor skills.

关键词： Training Somatosensory Visualization Robot kinematics Medical treatment Propioception Virtual reality Stroke (medical condition) Motors Real-time systems

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Network-based analysis to uncover drug-induced adverse side-effects

Network-based analysis to uncover drug-induced adverse side-...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Funari, Alessio Paci, Paola Conte, Federica Sapienza University of Rome Department of Translational and Precision Medicine Rome Italy National Research Council Institute for Systems Analysis and Computer Science 'Antonio Ruberti' Rome Italy Sapienza University of Rome Department of Computer Control and Management Engineering Rome Italy Karolinska Institutet Stockholm17177 Sweden

ISBN: (纸本)9798350337488

Despite the drug approval process consists of extremely rigorous clinical and preclinical studies, not all side effects are identified before its marketing, posing a significant risk to public health. Furthermore, considering the huge use of economic and human resources, in-silico predictive approaches for the identification of side effects are essential. In this study, we introduce a new method based on random walk with restart algorithm to delineate previously unidentified links between drugs and side effects, and we apply it on the drug-induced Asthma and long QT syndrome. We identified the genes potentially involved in the development of the analyzed side effect by comparing side-effect-related drugs with drugs not known to induce side effects. Analyzing the sets of genes most likely influenced by the perturbation of each individual drug, we observed that, on average, side-effect-related drugs perturb a higher percentage of genes involved in the development of side effects compared to side-effect-unrelated drugs. Based on this finding, we developed a classifier to explore all possible unknown associations between drugs and side effects. This method can be extended to the analysis of other side effects as well. © 2023 IEEE.

关键词： network medicine random walk side effect

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Optimal Energy Exchange of Two Electric Vehicle Charging Stations with Solar-Hydrogen-Battery Storage systems

Optimal Energy Exchange of Two Electric Vehicle Charging Sta...

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International Universities Power engineering Conference (UPEC)

作者： Lijia Duan Chun Sing Lai Gareth Taylor Xin Zhang Department of Electronic and Electrical Enginnering Brunel University London United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield United Kingdom

This paper presents an optimisation method for the direct energy exchange between two electric vehicle (EV) charging stations located in the UK. Each EV charging station consists of solar panels, hydrogen and battery energy storage systems (SHBS). The stations are interconnected through a energy exchange system that enables the transfer of excess energy from one station to the other. The objective function of SHBS charging stations is to minimize the capital and operation and maintenance costs of the stations. The system constraints are the power output of individual components, as well as the power balance between SHBS charging stations and EV charging demand. Genetic Algorithm is used to optimize the system, considering various factors such as the size of the solar panels and hydrogen storage tanks, the capacity of the electric vehicle chargers, and the amount of energy exchanged between the two stations. The optimized system yields substantial cost savings.

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A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

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IEEE/CAA Journal of automatica Sinica 2022年第5期9卷 812-833页

作者： Xinlei Yi Shengjun Zhang Tao Yang Tianyou Chai Karl Henrik Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technologyand also affiliated with the Digital FuturesStockholm 10044Sweden Department of Electrical Engineering University of North TexasDentonTX 76203 USA IEEE State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of n local cost functions by using local information exchange is *** problem is an important component of many machine learning techniques with data parallelism,such as deep learning and federated *** propose a distributed primal-dual stochastic gradient descent(SGD)algorithm,suitable for arbitrarily connected communication networks and any smooth(possibly nonconvex)cost *** show that the proposed algorithm achieves the linear speedup convergence rate O(1/(√nT))for general nonconvex cost functions and the linear speedup convergence rate O(1/(nT)) when the global cost function satisfies the Polyak-Lojasiewicz(P-L)condition,where T is the total number of *** also show that the output of the proposed algorithm with constant parameters linearly converges to a neighborhood of a global *** demonstrate through numerical experiments the efficiency of our algorithm in comparison with the baseline centralized SGD and recently proposed distributed SGD algorithms.

关键词： Distributed nonconvex optimization linear speedup Polyak-Lojasiewicz(P-L)condition primal-dual algorithm stochastic gradient descent

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On the Existence and Uniqueness of Steady State Solutions of a Class of Dynamic Hydraulic Networks via Actuator Placement

On the Existence and Uniqueness of Steady State Solutions of...

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IEEE Conference on Decision and control

作者： Mark Jeeninga Juan E. Machado Michele Cucuzzella Giacomo Como Jacquelien Scherpen Department of Automatic Control Lund University Lund Sweden Chair of Control Systems and Network Control Technology Faculty 3 Mechanical Engineering Electrical and Energy Systems Brandenburg University of Technology Cottbus - Senftenberg Cottbus Germany Department of Electrical Computer Science and Biomedical Engineering Univeristy of Pavia Pavia Italy Department of Mathematical Science “G.L. Lagrange” Politecnico di Torino Torino Italy Department of Automatic Control Lund University Faculty of Science and Engineering Jan C. Willems Center for Systems and Control ENTEG University of Groningen Groningen the Netherlands

In this paper, using tools from graph theory we provide verifiable necessary and sufficient conditions for the existence of a unique hydraulic equilibrium in district heating systems of meshed topology and containing multiple heat sources. Even though numerous publications have addressed the design of efficient algorithms for numerically finding hydraulic equilibria in the general context of water distribution networks, this is not the case for the analysis of existence and uniqueness. Moreover, most of the existing work dealing with these aspects exploit the equivalence between the nonlinear algebraic equations describing the hydraulic equilibria and the KKT conditions of a suitably defined nonlinear convex optimization problem. Differently, this paper proposes necessary and sufficient graph-theoretic conditions on the actuator placement for the existence and uniqueness of a hydraulic equilibrium, independent of the actuators' control objective. An example based on a representative district heating network is considered to illustrate the key aspects of our contribution, and an explicit formulation of the steady state solution is given for the case in which pressure drops through pipes are linear with respect to the flow rate.

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