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arXiv 2021年

作者： Czornik, Adam Makarov, Evgeniı Niezabitowski, Michal Popova, Svetlana Zaitsev, Vasilii Department of Automatic Control and Robotics Silesian University of Technology Gliwice44-100 Poland Institute of Mathematics National Academy of Sciences of Belarus Minsk220072 Belarus Udmurt State University Izhevsk426034 Russia

We investigate the behavior of the Lyapunov spectrum of a linear discrete-time system under the action of small perturbations in order to obtain some verifiable conditions for stability and openness of the Lyapunov spectrum. To this end we introduce the concepts of broken away solutions and splitted systems. The main results obtained are a necessary condition for stability and a sufficient condition for the openness of the Lyapunov spectrum, which is given in terms of the system itself. Finally, examples of using the obtained results are *** Codes 39A06, 39A22, 39A30 © 2021, CC BY.

关键词： Lyapunov functions

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CCTV based system for detection of anti-virus masks

CCTV based system for detection of anti-virus masks

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Kacper Podbucki Jakub Suder Tomasz Marciniak Adam Dąbrowski Division of Electronic Systems and Signal Processing Jana Pawła II 24 Poznan University of Technology Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań Poland

ISBN: (数字)9788362065394

ISBN: (纸本)9781728177465

This paper presents the use of neural networks to detect people with anti-virus masks. The algorithm allows to determine if a person has a correctly worn mask (covered nose and mouth). The use of neural networks has been compared with typical Haar cascade frontal face solutions available in the OpenCV library. The proposed solution has been checked for efficiency and precision, as well as for the minimum resolution requirements of the resulting facial image. The software works on still images as well as on video sequences from computer webcams and CCTV cameras.

关键词： Face recognition Neural networks Databases Image resolution Faces Face detection Software

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The Use of Various Neurostimulators in Therapy of Neurodegenerative Disorders – A Survey

The Use of Various Neurostimulators in Therapy of Neurodegen...

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Progress in Applied Electrical Engineering (PAEE)

作者： Aleksandra Kawala-Sterniuk Agata Gajos Mateusz Pawłowski Witold Libionka Władysław Piotr Duch Bartosz Pańczyszak Monika Stomal-Słowińska Michał Podpora Waldemar Bauer Adam Sudoł Mariusz Pelc Jarosław Zygarlicki Piotr Sterniuk Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Department of Neurosurgery "Vital Medic" Hospital Kluczbork Poland Department of Extrapyramidal Diseases Medical University of Łódź Łódź Poland Faculty of Health Sciences Wroclaw Medical University Wrocław Poland Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland Faculty of Natural Sciences and Technology University of Opole Opole Poland School Of Computing and Mathematical Sciences University of Greenwich London United Kindgom Center for Technology Transfer Opole University of Technology Opole Poland

ISBN: (数字)9781665455152

ISBN: (纸本)9781665455169

The use of neurostimulators in the treatment and therapy of neurodegenerative diseases is an alternative to pharmacological treatment. Unfortunately, most of these disorders are incurable, however, the use of neurostimulators can delay the onset of symptoms, the course of the disease and significantly improve the quality of life. Treatment with the use of neurostimulators also allows you to avoid side effects which usually accompany pharmacotherapy, or in order to replace it when prescribed medication is not working properly or not working at all. This paper focuses mainly on vagus nerve and deep brain stimulation.

关键词： Electrical engineering Deep brain stimulation Medical treatment Delays Diseases

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Robust 3D tracking control of an underactuated autonomous airship

arXiv

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arXiv 2020年

作者： Adamski, Wojciech Pazderski, Dariusz Herman, Przemysaw Institute of Automatic Control and Robotics Pozna University of Technology Piotrowo 3A Pozna60–965 Poland

The paper presents a new, robust control algorithm for position trajectory tracking in a 3D space, dedicated to underactuated airships. In order to take into account real characteristics of such vehicles, and to reflect practically motivated constraints, the algorithm assumes a highly uncertain system dynamics model. The tracking problem is solved in a uniform way, without dividing it into subtasks considered in 2D spaces, thanks to the introduction of an auxiliary tracking error. The proposed controller is based on the sliding mode approach. Its stability is investigated using Lyapunov theorem. Numerical simulations are conducted in order to verify properties of a closed-loop system for a generic model of the airship. Performance of the control system is examined via experiments in various scenarios using a prototype airship. The obtained results indicate that the control objectives are satisfied in practice with a reasonable accuracy. Moreover, it is shown that the controller is robust to some bounded additive measurement perturbations and delays in the control loop. Copyright © 2020, The Authors. All rights reserved.

关键词： Airships

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Achieving consensus in spite of stubbornness: time-varying concatenated Friedkin-Johnsen models

Achieving consensus in spite of stubbornness: time-varying c...

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IEEE Conference on Decision and control

作者： L. Wang C. Bernardo Y. Hong F. Vasca G. Shi C. Altafini Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China Group for Research on Automatic Control Engineering University of Sannio Benevento Italy Tongji University Shanghai China Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW Sydney Division of Automatic Control Linköping University Linköping Sweden

ISBN: (纸本)9781665436601

A concatenated Friedkin-Johnsen (FJ) model is a two time-scale opinion dynamics model in which stubborn agents discuss a sequence of issues. For each issue, a FJ model is adopted, and concatenation refers to the fact that the final opinion of the agents at issue s becomes the initial condition at issue s + 1. In this paper we deal with the case in which the system is open, i.e., the group of interacting agents changes at each issue, and so does their stubbornness. A concatenated FJ model can in this case be represented as an infinite product of stochastic matrices. For such system, we obtain sufficient conditions under which the opinions of the agents converge to consensus.

关键词： Sufficient conditions Conferences Stochastic processes

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Selection of Methods for Intuitive, Haptic control of the Underwater Vehicle’s Manipulator 20th

Selection of Methods for Intuitive, Haptic Control of the Un...

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20th Polish control Conference, PCC 2020

作者： Grzejszczak, Tomasz Babiarz, Artur Bieda, Robert Jaskot, Krzysztof Kozyra, Andrzej Ściegienka, Piotr Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Gliwice44-100 Poland SR Robotics sp. z o.o. ul. Karoliny 4 Katowice40-186 Poland

ISBN: (纸本)9783030509354

This paper is the early report of available market and scientific solutions allowing intuitive control. Manipulator control is presented in form of the Human Machine Interaction loop that describes both machine possibilities of sensing the human control and human possibilities of sensing the machine state. The survey is presented in form of the description and discussion of the advantages, disadvantages and usability of the available solutions. The aim of the research is to chose the proper path of development of the new way of intuitive control. © 2020, Springer Nature Switzerland AG.

关键词： Manipulators

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Odour Concentrations Prediction Based on Odorants Concentrations from Biosolid Emissions

SSRN

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SSRN 2022年

作者： Barczak, Radoslaw J. Możaryn, Jakub Fisher, Ruth M. Stuetz, Richard M. Faculty of Chemistry University of Warsaw 1 Pasteura Street Warsaw02-093 Poland UNSW Water Research Centre School of Civil and Environmental Engineering UNSW Sydney Australia Faculty of Building Services Hydro and Environmental Engineering Warsaw University of Technology Poland Faculty of Mechatronics Institute of Automatic Control and Robotics Warsaw University of Technology Poland

Biosolids storage areas are a significant contributor to wastewater treatment plant (WWTPs) odour emissions which can cause sensorial impact to surrounding communities. Most odour impact regulations are based on odour concentration (COD) measurements determined by dynamic olfactometry. Understanding the relationship between odorants concentrations and COD in the biosolids emission is important to identify how the measurement and monitoring can be conducted using analytical rather than sensorial techniques. Some of the odorants are unknown in biosolid emissions, increasing the uncertainty in predicting COD. In this study, emissions from 56 biosolid samples collected from two WWTPs located in Sydney, Australia, were analysed by analytical and sensorial methods, including olfactory detection port (ODP) and dynamic olfactometry. Concentrations of 25 odorants and two ordinal variables represented odour events detected by ODP assessors were linked to COD values. Bayesian Model Averaging and Variable Selection with Bayesian Adaptive Sampling were applied to model the relation between COD and odorants concentrations. Results indicate the usability of the probabilistic methods and nonlinear transformations in modelling the odour concentrations based on odorants concentrations from biosolids emission and the accuracy of a small dataset. © 2022, The Authors. All rights reserved.

关键词： Odors

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An Innovative Smart Irrigation Using Embedded and Regression-Based Machine Learning Technologies for Improving Water Security and Sustainability

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IEEE Access 2025年 13卷 100731-100751页

作者： Abdennabi Morchid Abdennacer Elbasri Zahra Oughannou Hassan Qjidaa Rachid El Alami Badre Bossoufi Saleh Mobayen Paweł Skruch LIMAS Laboratory Faculty of Sciences Dhar El Mahraz Sidi Mohamed Ben Abdellah (SMBA) University Fes Morocco Department of Data Science Mundiapolis University of Casablanca Campus Nouaceur Casablanca Morocco Innovation in Mathematics and Intelligent Systems (IMIS) Laboratory Ibn Zohr University Agadir Morocco Systems and Sustainable Environment Laboratory (SED) Faculty of Engineering Sciences (FSI) Private University of Fez (UPF) Fes Morocco Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliu Taiwan Energy Systems Research Center Khazar University Baku Azerbaijan Department of Automatic Control and Robotics AGH University of Science and Technology Kraków Poland

Global agriculture is facing major challenges such as food security, sustainable water management, and the preservation of natural resources. Water scarcity, exacerbated by climate change, requires adopting more efficient agricultural practices. Traditional irrigation systems, often imprecise, contribute to water wastage. The use of embedded systems and machine learning offers a solution for optimizing irrigation according to local conditions and actual crop needs while contributing to food security and environmental sustainability. This study proposes an innovative approach to irrigation management, integrating real-time data and predictive models to improve irrigation efficiency. This study proposes an irrigation system based on embedded systems, using sensors and algorithms to collect and analyze data in order to optimize water management. The system adjusts irrigation levels according to specific crop needs, thus contributing to more sustainable water management. Using ML algorithms like linear regression algorithms to model the relationships between environmental factors and crop water requirements, enabling accurate prediction of required irrigation levels based on data collected by sensors. The use of embedded systems such as the ESP32, combined with temperature, humidity, and water level sensors, has enabled the development of an autonomous and efficient system for collecting data in real-time and processing it for decision-making. The proposed model has an MAE of 0.8434, an RMSE of 0.8434, and a coefficient (R2 Score) of 0.4044, offering soil moisture prediction accuracy. Furthermore, the training time of our model is 0.00253 seconds, while the prediction time is 0.00117 seconds. These results show not only the performance of the proposed model in terms of accuracy but also its computational efficiency, outperforming some of the studies mentioned. The results of the study show a significant reduction in water consumption, with a marked improvement in water

关键词： Climate change Embedded systems Smart agriculture Irrigation Food security Optimization methods Machine learning Machine learning algorithms Sustainable development Water resources Water monitoring Environmental management

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Odour Concentrations Prediction Based on Odorants Concentrations from Biosolid Emissions

SSRN

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SSRN 2022年

关键词： Odors

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Generic Sensor Model for Object Detection Algorithms Validation 20th

Generic Sensor Model for Object Detection Algorithms Validat...

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20th Polish control Conference, PCC 2020

作者： Lelowicz, Kamil Jasiński, Michal Piątek, Marcin Department of Automatic Control and Robotics AGH University of Science and Technology al. A. Mickiewicza 30 Kraków30-059 Poland APTIV Services Poland S.A. ul. Podgorki Tynieckie 2 Kraków30-399 Poland

ISBN: (纸本)9783030509354

In the artificial intelligence era of perception algorithms being used in the state-of-the-art Advance Driver Assistance Systems, algorithm validation is not an easy task, mainly due to the amount of sensor data that must be processed at once. To provide the highest possible safety level of the solution, algorithm performance must be assessed in various difficult conditions. To address this problem, a novel Generic Sensor Model algorithm is presented, which can be directly incorporated in performance analysis of the perception algorithm in highly occluded driving scenarios. In this paper, the Generic Sensor Model algorithm is comprehensively described and its usefulness and robustness are proven with a set of experiments. © 2020, Springer Nature Switzerland AG.

关键词： Object detection

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