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arXiv 2021年

作者： Esterhuizen, Willem Wang, Qing-Guo Technische Universität Chemnitz Automatic Control & System Dynamics Laboratory Germany Institute for Intelligent Systems Faculty of Engineering and the Built Environment University of Johannesburg South Africa

In this paper a novel approach is presented for control design with guaranteed transient performance for multiple-input multiple-output discrete-time linear polytopic difference inclusions. We establish a theorem that gives necessary and sufficient conditions for the state to evolve from one polyhedral subset of the state-space to another. Then we present an algorithm which constructs a time-varying output feedback law which guarantees that the state evolves within a time-varying polyhedral target-tube specifying the system’s desired transient performance. We present generalisations involving constraints on the control, and a bounded additive disturbance term. Our formulation is very general and includes reference tracking with any desired transient behaviour in the face of disturbances, as specified, for example, by the most popular step response specifications. The approach is demonstrated by an example involving the control of water levels in two coupled *** Codes 93C35, 93C05, 93B52 © 2021, CC BY-NC-ND.

关键词： Transient analysis

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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

arXiv

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arXiv 2024年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Grau, Antoni Zhang, Fuquan The College of Computer and Big Data Fuzhou University Fuzhou China The Department of Automatic Control Polytechnic University of Catalonia Barcelona Spain The New Engineering Industry College Putian University Putian China School of Computer and Artificial Intelligence Zhengzhou University China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China College of Computer and Control Engineering Minjiang University Fuzhou China Key Laboratory of Sichuan Province Sichuan Conservatory of Music Chengdu China Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Minjiang University Fuzhou China Fujian Polytechnic Normal University Fujian Province University Fuzhou China

Driver drowsiness electroencephalography (EEG) signal monitoring can timely alert drivers of their drowsiness status, thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end lightweight dual graph convolutional network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. Furthermore, to deploy our method on the fourth-generation Raspberry Pi, we utilize Adaptive Pruning Optimization (APO) on both channels and neurons, reducing inference latency by almost half. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization compared to existing state-of-the-art algorithms. All our source code can be found at https://***/BryantDom/Driver-Drowsiness-Monitoring. Copyright © 2024, The Authors. All rights reserved.

关键词： Electroencephalography

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Improving EEG-based error detection using relative peak features

Improving EEG-based error detection using relative peak feat...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Adrian L. Ashley Mahnaz Arvaneh Automatic control and system Engineering Department University of Sheffield Sheffield United Kingdom

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

A brain-computer interface (BCI) potentially enables a severely disabled person to communicate using brain signals. automatic detection of error-related potentials (ErrPs) in electroencephalograph (EEG) could improve BCI performance by allowing to correct the erroneous action made by the machine. However, the current low accuracy in detecting ErrPs, particularly in some users, can reduce its potential benefits. The paper addresses this problem by proposing a novel relative peak feature (RPF) selection method to improve performance and accuracy for recognising an ErrP in the EEG. Using data collected from 29 participants with a mean age of 24.14 years the relative peak features yielded an average across all classifiers of 81.63% accuracy in detecting the erroneous events and an average 78.87 % accuracy in detecting the correct events, using KNN, SVM and LDA classifiers. In comparison to the temporal feature selection, there was a gain in performance in all classifiers of 17.85% for error accuracy and a reduction of -6.16% for correct accuracy Specifically; our proposed RPF used significantly reduced the number of features by 91.7% when compared with the state of the art temporal *** the future, this work will improve the human-robot interaction by improving the accuracy of detecting errors that enable the BCI to correct any mistakes.

关键词： Electroencephalography Feature extraction Task analysis Support vector machines Electrodes Training Electric potential

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A new force profile signal for a convex solution of muscle force estimation from electromyographic signals*

A new force profile signal for a convex solution of muscle f...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Mehdi Shirzadi Arezoo Mirshamsi Alp Eşrefoğlu Monica Rojas-Martínez Hamid Reza Marateb Miquel Angel Mañanas Taian Vieira Department of Automatic Control (ESAII) Biomedical Engineering Research Centre (CREB) Universitat Politèncicna de Catalunya (UPC) Barcelona Spain Biomedical Engineering Department Engineering Faculty University of Isfahan Isfahan Iran Laboratory of Applied Biology & Research Unit in Applied Neurophysiology (LABNeuro) – Université Libre de Bruxelles Brussels Belgium CIBER of Bioengineering Biomaterilas and Nanomedicine (CIBER-BBN) Madrid Spain Department of Electronics and Telecommunication Laboratory for Engineering of the Neuromuscular System (LISiN) PolitoBIOMed Lab – Politecnico di Torino Turin Italy

High-Density Surface Electromyography (HD-sEMG) is a non-invasive technique for measuring the electrical activity of a muscle with multiple, closely spaced electrodes. Estimation of muscle force is one of the applications of HD-sEMG. Usually, validating different EMG-Force models entails simple movements limited to laboratory settings. The validity of these models in more ecological conditions, requesting force production over a wide frequency band, remains unknown. In this study, we, therefore, compare the results of force prediction using four different types of input force profiles that can be representative of daily life activities, and we investigate whether the crest factor of these different input signals affects force prediction. For predicting the force from sEMG signals, we used our real-time and convex methods. HD-sEMG signals were recorded with 144 channels from the biceps brachii, brachioradialis, and triceps (long, lateral, and medial head) muscles of 24 healthy subjects during random signal, random phase, Schroeder phase, and minimum crest factor (crestmin) signal. The correlation and coefficient of determination (R 2 ) between measured and predicted forces were calculated for the different force feedback profiles. The crestmin signal showed significantly better results based on statistical tests (P-value < 0.05), with correlation and R 2 equal to 0.92±0.03 and 0.86±0.05, respectively. The results demonstrate that the crest factor of input signals is a crucial parameter that can impact the performance of EMG-Force models and must be considered during *** Relevance— This study demonstrates that lower crest factor multisine force profiles result in improved fitness for force prediction and can be used as an alternative to random signals.

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Intelligent sitting postural anomaly detection system for wheelchair users with unsupervised techniques

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Digital Communications and Networks 2024年

作者： Patrick Vermander Aitziber Mancisidor Raffaele Gravina Itziar Cabanes Giancarlo Fortino Department of Automatic Control and System Engineering University of the Basque Country (UPV/EHU) Bilbao 48013 Spain Department of Informatics Modeling Electronics and Systems Engineering University of Calabria (UNICAL) Rende 87036 Italy

Detecting sitting posture abnormalities in wheelchair users enables early identification of changes in their functional status. To date, this detection has relied on in-person observation by medical specialists. However, given the challenges faced by health specialists to carry out continuous monitoring, the development of an intelligent anomaly detection system is proposed. Unlike other authors, where they use supervised techniques, this work proposes using unsupervised techniques due to the advantages they offer. These advantages include the lack of prior labeling of data, and the detection of anomalies previously not contemplated, among others. In the present work, an individualized methodology consisting of two phases is developed: characterizing the normal sitting pattern and determining abnormal samples. An analysis has been carried out between different unsupervised techniques to study which ones are more suitable for postural diagnosis. It can be concluded, among other aspects, that the utilization of dimensionality reduction techniques leads to improved results. Moreover, the normality characterization phase is deemed necessary for enhancing the system's learning capabilities. Additionally, employing an individualized approach to the model aids in capturing the particularities of the various pathologies present among subjects.

关键词： Sitting posture monitoring Anomaly detection Assistive technology Pressure sensors Unsupervised techniques Individualization Wheelchair

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Study of photophysical properties of Cdq2 thin film

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Materials Today: Proceedings 2022年 66卷 202-204页

作者： Lougdali, M. El Kouari, Y. Anoua, R. Zazoui, M. El Oudghiri-Idrissi, I. Abboud, Y. Zawadzka, A. Sahraoui, B. Laboratory of Materials Energy and Control System Faculty of Sciences and Technology Hassan II University of Casablanca Mohammedia B.P 146 Morocco Department of Automatic and Measurement Faculty of Physics Astronomy and Informatics Nicolaus Copernicus University Torun Poland Laboratory of Engineering Sciences for Energy National School of Applied Sciences of El Jadida El Jadida BP 1166 Morocco Faculty of Sciences Ben M'sik University of Hassan II of Casablanca Casablanca Morocco Centre for Modern Interdisciplinary Technologies Nicolaus Copernicus University Wilenska 4 Torun 87-100 Poland MOLTECH-Anjou UMR 6200 CNRS UNIV Angers 2 bd Lavoisier Angers 49045 France

In this work, the morphological and optical properties of the cadmium (II) bis(8-hydroxyquinoline) (Cdq2) thin film are presented. The film was elaborated by physical deposition technique. The Atomic Force Microscopy (AFM) image shows a homogenous surface. The transmittance was measured in the range of 300–1200 nm with UV–visible spectroscopy. The emission of the film was characterized via the photoluminescence spectroscopy, a strong luminescence has been found. The measurements done at low temperatures show a decrease of the intensity of luminescence in the temperature range of 77–300 K. © 2022

关键词： Thin films

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Computational characterization of a Gurney flap on a DU91(2)W250 airfoil

Computational characterization of a Gurney flap on a DU91(2)...

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2018 International Conference on Materials and Energy, ICOME 2018

作者： Fernandez-Gamiz, Unai Errasti, Iñigo Zulueta, Ekaitz Lopez Guede, José Manuel Boyano, Ana Nuclear Eng. and Fluid Mechanics Dept. Vitoria01006 Spain Automatic Control and System Engineering Dept. Vitoria01006 Spain Mechanical Engineering Dept. Vitoria01006 Spain

The considerable increase of wind turbine rotor size and weight in the last years has made impossible to control as they were controlled 20 years ago. The cost of energy is an essential role to maintain this type of energy as a viable alternative in economic terms with traditional or other renewable energies. Through the last decades many different flow control devices have been developed. Most of them were shaped for aeronautical issues and this was its first research application. Currently researchers are working to optimize and introduce these types of devices in multi megawatt wind turbines. Gurney flap (GF) is a vane perpendicular to the airfoil surface with a size between 0.1 and 3% of the airfoil chord length, placed in the lower or upper side of the airfoil close to the trailing edge of the airfoil. When GFs are appropriately designed, they increase the total lift of the airfoil while reducing the drag. Thanks to the implementation of the of this flow control device the efficiency of a wind turbine improves, which results on an increase in the power generation. © The Authors, published by EDP Sciences, 2020.

关键词： Airfoils

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Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

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arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

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Active Flow control on Airfoils by Reinforcement Learning

SSRN

引用

SSRN 2023年

作者： Portal-Porras, Koldo Fernandez-Gamiz, Unai Zulueta, Ekaitz Garcia-Fernandez, Roberto Berrizbeitia, Saioa Etxebarria Nuclear Engineering and Fluid Mechanics Department Faculty of Engineering of Vitoria-Gasteiz University of the Basque Country UPV/EHU Nieves Cano 12 Araba Vitoria-Gasteiz01006 Spain Automatic Control and System Engineering Department Faculty of Engineering of Vitoria-Gasteiz University of the Basque Country UPV/EHU Nieves Cano 12 Araba Vitoria-Gasteiz01006 Spain Sunsundegui S.A. Poligono Ibarrea s/n Navarra Altsasu31800 Spain Mechanical Engineering Department Faculty of Engineering of Vitoria-Gasteiz University of the Basque Country UPV/EHU Nieves Cano 12 Araba Vitoria-Gasteiz01006 Spain

In recent years, wind energy is gaining importance, with the aim of achieving a clean and sustainable energy model. However, an enhancement in wind turbine performance is still required to compete with traditional energy sources. The implementation of flow control devices in airfoils is one of the most common solutions to achieve this improvement. Among flow control devices several alternatives are available, but devices with reactive control are the most effective, due to their capacity to adapt to instantaneous conditions of the flow. This study proposes a control strategy based on a Reinforcement Learning (RL) agent to effectively govern the motion of a rotating flap implemented on a NACA0012 airfoil. With this objective, first different Computational Fluid Dynamics (CFD) simulations are conducted to gather data about the tested case. Then, a numerical model based on Artificial Neural Networks (ANN) is developed to model the discussed case. Finally, the RL agent is trained and tested under different conditions. The results show that the trained RL agent is able to provide a fast and reliable response for every tested condition, setting the adequate position of the flap and obtaining an appropriate aerodynamic performance of the airfoil. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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On inf-convolution-based robust practical stabilization under computational uncertainty

arXiv

引用

arXiv 2021年

作者： Schmidt, Patrick Osinenko, Pavel Streif, Stefan Technische Universität Chemnitz Automatic Control and System Dynamics Lab Chemnitz09126 Germany Computational and Data Science and Engineering Center Skolkovo Institute of Science and Technology Moscow143026 Russia

This work is concerned with practical stabilization of nonlinear systems by means of inf-convolution-based sample-and-hold control. It is a fairly general stabilization technique based on a generic non-smooth control Lyapunov function (CLF) and robust to actuator uncertainty, measurement noise, etc. The stabilization technique itself involves computation of descent directions of the CLF. It turns out that non-exact realization of this computation leads not just to a quantitative, but also qualitative obstruction in the sense that the result of the computation might fail to be a descent direction altogether and there is also no straightforward way to relate it to a descent direction. Disturbance, primarily measurement noise, complicate the described issue even more. This work suggests a modified inf-convolution-based control that is robust w. r. t. system and measurement noise, as well as computational uncertainty. The assumptions on the CLF are mild, as, e. g., any piece-wise smooth function, which often results from a numerical LF/CLF construction, satisfies them. A computational study with a three-wheel robot with dynamical steering and throttle under various tolerances w. r. t. computational uncertainty demonstrates the relevance of the addressed issue and the necessity of modifying the used stabilization technique. Similar analyses may be extended to other methods which involve optimization, such as Dini aiming or steepest descent. © 2021, CC BY-NC-ND.

关键词： Nonlinear systems

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