473 research outputs found

    Fractional multi-loop active disturbance rejection control for a lower knee exoskeleton system

    Get PDF
    Rehabilitation Exoskeleton is becoming more and more important in physiotherapists’ routine work. To improve the treatment performance, such as reducing the recovery period and/or monitoring and reacting to unpredictable situations, the rehabilitation manipulators need to help the patients in various physical trainings. A special case of the active disturbance rejection control (ADRC) is applied to govern a proper realisation of basic limb rehabilitation trainings. The experimental study is performed on a model of a flexible joint manipulator, whose behaviour resembles a real exoskeleton rehabilitation device (a one-degree-of-freedom, rigid-link, flexible-joint manipulator). The fractional (FADRC) is an unconventional model-independent approach, acknowledged as an effective controller in the existence of total plant uncertainties, and these uncertainties are inclusive of the total disturbances and unknown dynamics of the plant. In this work, three FADRC schemes are used, the first one using a fractional state observer (FSO), or FADRC1, second one using a fractional proportional-derivative controller (FPD), or FADRC2, and the third one a Multi-loop fractional in PD-loop controller and the observer-loop (Feedforward and Feedback), or FADRC3. The simulated Exoskeleton system is subjected to a noise disturbance and the FADRC3 shows the effectiveness to compensate all these effects and satisfies the desired position when compared with FADRC1 and FADRC2. The design and simulation were carried out in MATLAB/Simulink

    Surgical Subtask Automation for Intraluminal Procedures using Deep Reinforcement Learning

    Get PDF
    Intraluminal procedures have opened up a new sub-field of minimally invasive surgery that use flexible instruments to navigate through complex luminal structures of the body, resulting in reduced invasiveness and improved patient benefits. One of the major challenges in this field is the accurate and precise control of the instrument inside the human body. Robotics has emerged as a promising solution to this problem. However, to achieve successful robotic intraluminal interventions, the control of the instrument needs to be automated to a large extent. The thesis first examines the state-of-the-art in intraluminal surgical robotics and identifies the key challenges in this field, which include the need for safe and effective tool manipulation, and the ability to adapt to unexpected changes in the luminal environment. To address these challenges, the thesis proposes several levels of autonomy that enable the robotic system to perform individual subtasks autonomously, while still allowing the surgeon to retain overall control of the procedure. The approach facilitates the development of specialized algorithms such as Deep Reinforcement Learning (DRL) for subtasks like navigation and tissue manipulation to produce robust surgical gestures. Additionally, the thesis proposes a safety framework that provides formal guarantees to prevent risky actions. The presented approaches are evaluated through a series of experiments using simulation and robotic platforms. The experiments demonstrate that subtask automation can improve the accuracy and efficiency of tool positioning and tissue manipulation, while also reducing the cognitive load on the surgeon. The results of this research have the potential to improve the reliability and safety of intraluminal surgical interventions, ultimately leading to better outcomes for patients and surgeons

    Orvosképzés 2023

    Get PDF

    Adaptation of the human nervous system for self-aware secure mobile and IoT systems

    Get PDF
    IT systems have been deployed across several domains, such as hospitals and industries, for the management of information and operations. These systems will soon be ubiquitous in every field due to the transition towards the Internet of Things (IoT). The IoT brings devices with sensory functions into IT systems through the process of internetworking. The sensory functions of IoT enable them to generate and process information automatically, either without human contribution or having the least human interaction possible aside from the information and operations management tasks. Security is crucial as it prevents system exploitation. Security has been employed after system implementation, and has rarely been considered as a part of the system. In this dissertation, a novel solution based on a biological approach is presented to embed security as an inalienable part of the system. The proposed solution, in the form of a prototype of the system, is based on the functions of the human nervous system (HNS) in protecting its host from the impacts caused by external or internal changes. The contributions of this work are the derivation of a new system architecture from HNS functionalities and experiments that prove the implementation feasibility and efficiency of the proposed HNS-based architecture through prototype development and evaluation. The first contribution of this work is the adaptation of human nervous system functions to propose a new architecture for IT systems security. The major organs and functions of the HNS are investigated and critical areas are identified for the adaptation process. Several individual system components with similar functions to the HNS are created and grouped to form individual subsystems. The relationship between these components is established in a similar way as in the HNS, resulting in a new system architecture that includes security as a core component. The adapted HNS-based system architecture is employed in two the experiments prove its implementation capability, enhancement of security, and overall system operations. The second contribution is the implementation of the proposed HNS-based security solution in the IoT test-bed. A temperature-monitoring application with an intrusion detection system (IDS) based on the proposed HNS architecture is implemented as part of the test-bed experiment. Contiki OS is used for implementation, and the 6LoWPAN stack is modified during the development process. The application, together with the IDS, has a brain subsystem (BrSS), a spinal cord subsystem (SCSS), and other functions similar to the HNS whose names are changed. The HNS functions are shared between an edge router and resource-constrained devices (RCDs) during implementation. The experiment is evaluated in both test-bed and simulation environments. Zolertia Z1 nodes are used to form a 6LoWPAN network, and an edge router is created by combining Pandaboard and Z1 node for a test-bed setup. Two networks with different numbers of sensor nodes are used as simulation environments in the Cooja simulator. The third contribution of this dissertation is the implementation of the proposed HNS-based architecture in the mobile platform. In this phase, the Android operating system (OS) is selected for experimentation, and the proposed HNS-based architecture is specifically tailored for Android. A context-based dynamically reconfigurable access control system (CoDRA) is developed based on the principles of the refined HNS architecture. CoDRA is implemented through customization of Android OS and evaluated under real-time usage conditions in test-bed environments. During the evaluation, the implemented prototype mimicked the nature of the HNS in securing the application under threat with negligible resource requirements and solved the problems in existing approaches by embedding security within the system. Furthermore, the results of the experiments highlighted the retention of HNS functions after refinement for different IT application areas, especially the IoT, due to its resource-constrained nature, and the implementable capability of our proposed HNS architecture.--- IT-järjestelmiä hyödynnetään tiedon ja toimintojen hallinnassa useilla aloilla, kuten sairaaloissa ja teollisuudessa. Siirtyminen kohti esineiden Internetiä (Internet of Things, IoT) tuo tällaiset laitteet yhä kiinteämmäksi osaksi jokapäiväistä elämää. IT-järjestelmiin liitettyjen IoT-laitteiden sensoritoiminnot mahdollistavat tiedon automaattisen havainnoinnin ja käsittelyn osana suurempaa järjestelmää jopa täysin ilman ihmisen myötävaikutusta, poislukien mahdolliset ylläpito- ja hallintatoimenpiteet. Turvallisuus on ratkaisevan tärkeää IT-järjestelmien luvattoman käytön estämiseksi. Valitettavan usein järjestelmäsuunnittelussa turvallisuus ei ole osana ydinsuunnitteluprosessia, vaan otetaan huomioon vasta käyttöönoton jälkeen. Tässä väitöskirjassa esitellään uudenlainen biologiseen lähestymistapaan perustuva ratkaisu, jolla turvallisuus voidaan sisällyttää erottamattomaksi osaksi järjestelmää. Ehdotettu prototyyppiratkaisu perustuu ihmisen hermoston toimintaan tilanteessa, jossa se suojelee isäntäänsä ulkoisten tai sisäisten muutosten vaikutuksilta. Tämän työn keskeiset tulokset ovat uuden järjestelmäarkkitehtuurin johtaminen ihmisen hermoston toimintaperiaatteesta sekä tällaisen järjestelmän toteutettavuuden ja tehokkuuden arviointi kokeellisen prototyypin kehittämisen ja toiminnan arvioinnin avulla. Tämän väitöskirjan ensimmäinen kontribuutio on ihmisen hermoston toimintoihin perustuva IT-järjestelmäarkkitehtuuri. Tutkimuksessa arvioidaan ihmisen hermoston toimintaa ja tunnistetaan keskeiset toiminnot ja toiminnallisuudet, jotka mall-innetaan osaksi kehitettävää järjestelmää luomalla näitä vastaavat järjestelmäkomponentit. Nä-istä kootaan toiminnallisuudeltaan hermostoa vastaavat osajärjestelmät, joiden keskinäinen toiminta mallintaa ihmisen hermoston toimintaa. Näin luodaan arkkitehtuuri, jonka keskeisenä komponenttina on turvallisuus. Tämän pohjalta toteutetaan kaksi prototyyppijärjestelmää, joiden avulla arvioidaan arkkitehtuurin toteutuskelpoisuutta, turvallisuutta sekä toimintakykyä. Toinen kontribuutio on esitetyn hermostopohjaisen turvallisuusratkaisun toteuttaminen IoT-testialustalla. Kehitettyyn arkkitehtuuriin perustuva ja tunkeutumisen estojärjestelmän (intrusion detection system, IDS) sisältävä lämpötilan seurantasovellus toteutetaan käyttäen Contiki OS -käytöjärjestelmää. 6LoWPAN protokollapinoa muokataan tarpeen mukaan kehitysprosessin aikana. IDS:n lisäksi sovellukseen kuuluu aivo-osajärjestelmä (Brain subsystem, BrSS), selkäydinosajärjestelmä (Spinal cord subsystem, SCSS), sekä muita hermoston kaltaisia toimintoja. Nämä toiminnot jaetaan reunareitittimen ja resurssirajoitteisten laitteiden kesken. Tuloksia arvioidaan sekä simulaatioiden että testialustan tulosten perusteella. Testialustaa varten 6LoWPAN verkon toteutukseen valittiin Zolertia Z1 ja reunareititin on toteutettu Pandaboardin ja Z1:n yhdistelmällä. Cooja-simulaattorissa käytettiin mallinnukseen ymp-äristönä kahta erillistä ja erikokoisuta sensoriverkkoa. Kolmas tämän väitöskirjan kontribuutio on kehitetyn hermostopohjaisen arkkitehtuurin toteuttaminen mobiilialustassa. Toteutuksen alustaksi valitaan Android-käyttöjärjestelmä, ja kehitetty arkkitehtuuri räätälöidään Androidille. Tuloksena on kontekstipohjainen dynaamisesti uudelleen konfiguroitava pääsynvalvontajärjestelmä (context-based dynamically reconfigurable access control system, CoDRA). CoDRA toteutetaan mukauttamalla Androidin käyttöjärjestelmää ja toteutuksen toimivuutta arvioidaan reaaliaikaisissa käyttöolosuhteissa testialustaympäristöissä. Toteutusta arvioitaessa havaittiin, että kehitetty prototyyppi jäljitteli ihmishermoston toimintaa kohdesovelluksen suojaamisessa, suoriutui tehtävästään vähäisillä resurssivaatimuksilla ja onnistui sisällyttämään turvallisuuden järjestelmän ydintoimintoihin. Tulokset osoittivat, että tämän tyyppinen järjestelmä on toteutettavissa sekä sen, että järjestelmän hermostonkaltainen toiminnallisuus säilyy siirryttäessä sovellusalueelta toiselle, erityisesti resursseiltaan rajoittuneissa IoT-järjestelmissä

    Onduleur quasi-Z-source pour un système de traction de véhicules électriques à sources multiples : contrôle et gestion

    Get PDF
    Abstract: Power electronics play a fundamental role and help to achieve the new goals of the automobiles in terms of energy economy and environment. The power electronic converters are the key elements which interface their power sources to the drivetrain of the electric vehicle (EV). They contribute to obtaining high efficiency and performance in power systems. However, traditional inverters such as voltage-source, current-source inverters and conventional two-stage inverters present some conceptual limitations. Consequently, many research efforts have been focused on developing new power electronic converters suitable for EVs application. In order to develop and enhance the performance of commercial multiple sources EV, this dissertation aims to select and to control the impedance source inverter and to provide management approaches for multiple sources EV traction system. A concise review of the main existing topologies of impedance source inverters has been presented. That enables to select QZSI (quasi-Z-source inverter) topology as promising architectures with better performance and reliability. The comparative study between the bidirectional conventional two-stage inverter and QZSI for EV applications has been presented. Furthermore, comparative study between different powertrain topologies regarding batteries aging index factors for an off-road EV has been explored. These studies permit to prove that QZSI topology represents a good candidate to be used in multi-source EV system. For improving the performance of QZSI applied to EVs, optimized fractional order PI (FOPI) controllers for QZSI is designed with the ant colony optimization algorithm (ACO-NM) to obtain more suitable aging performance index values for the battery. Moreover, this thesis proposes a hybrid energy storage system (HESS) for EVs to allow an efficient energy use of the battery for a longer distance coverage. Optimized FOPI controller and the finite control set model predictive controller (FCS-MPC) for HESS using bidirectional QZSI is applied for the multi-source EV. The flux-weakening controller has been designed to provide a correct operation with the maximum available torque at any speed within current and voltage limits. Simulation investigations are performed to verify the topologies studied and the efficacity of the proposed controller structure with the bidirectional QZSI. Furthermore, Opal-RT-based real-time simulation has been implemented to validate the effectiveness of the proposed HESS control strategy. The results confirm the EV performance enhancement with the addition of supercapacitors using the proposed control configuration, allowing the efficient use of battery energy with the reduction of root-mean-square value, the mean value, and the standard deviation by 57%, 59%, and 27%, respectively, of battery current compared to the battery-only based inverter.L'électronique de puissance joue un rôle fondamental et contribue à atteindre les nouveaux objectifs de l'automobile en termes d'économie d'énergie et d'environnement. Les convertisseurs d’électroniques de puissance sont considérés comme les éléments clés qui interfacent leurs sources d'alimentation avec la chaîne de traction du véhicule électrique (VE). Ils contribuent à obtenir une efficacité et des performances élevées dans les systèmes électriques. Cependant, les onduleurs traditionnels tels que les onduleurs à source de tension, les onduleurs à source de courant et les onduleurs conventionnels à deux étages qui constituent les onduleurs les plus couramment utilisés, présentent certaines limitations conceptuelles. Par conséquent, de nombreux efforts de recherche se sont concentrés sur le développement de nouveaux convertisseurs d’électroniques de puissance adaptés à l'application aux véhicules électriques. Afin de développer et d'améliorer les performances des VEs à sources multiples commerciales, cette thèse vise à sélectionner, contrôler l'onduleur à source impédante et fournit une approche de gestion pour l'application du système de traction du VE à sources multiples. Une revue concise des principales topologies existantes d'onduleur à source impédante a été présentée. Cela a permis de sélectionner la topologie de l’onduleur quasi-Z-source (QZS) comme architectures prometteuses pouvant être utilisées dans les véhicules électriques, avec de meilleures performances et de fiabilité. L'étude comparative entre l'onduleur bidirectionnel conventionnel à deux étages et de celui à QZS pour les applications du VE a été présentée. En outre, une étude comparative entre différentes topologies de groupes motopropulseurs concernant les facteurs d'indice de vieillissement des batteries pour une application du VE hors route a été explorée. Ces études ont permis de prouver que la topologie de l’onduleur QZS représente une bonne topologie candidate à utiliser dans un système de VE à sources multiples. Pour améliorer les performances de l’onduleur QZS appliquées aux véhicules électriques, des contrôleurs PI d'ordre fractionnaire (PIOF) optimisés pour l’onduleur QZS sont conçus avec l'algorithme de colonies de fourmis afin d'obtenir des valeurs d'indice de performance de vieillissement plus appropriées pour la batterie. De plus, cette thèse propose un système de stockage d'énergie hybride (SSEH) pour le VE afin de permettre une utilisation efficace de l'énergie de la batterie pour une couverture de distance plus longue et une extension de son autonomie. L’optimisation du contrôleur PIOF et du contrôleur par modèle prédictif d'ensemble de contrôle fini (CMP-ECF) pour l’onduleur QZS bidirectionnel a été appliqué au VE à sources multiples avec des approches de gestion appuyées par des règles. Le contrôleur d'affaiblissement de flux magnétique du moteur a été conçu pour fournir un fonctionnement correct avec le couple maximal disponible à n'importe quelle vitesse dans les limites de courant et de tension. Des investigations et des simulations sont effectuées pour vérifier les différentes topologies étudiées et l'efficacité de la structure de contrôleur proposée avec l’onduleur QZS bidirectionnel. De plus, une simulation en temps réel basée sur Opal-RT a été mise en œuvre pour valider l'efficacité de la stratégie de contrôle SSEH proposée. Les résultats confirment l'amélioration des performances du VE avec l'ajout d'un supercondensateur utilisant la configuration du contrôle proposée, permettant une utilisation efficace de l'énergie de la batterie avec une réduction de la valeur moyenne quadratique, de la valeur moyenne et de l'écart type de 57%, 59% et 27%, respectivement, du courant de la batterie par rapport à l'onduleur connecté directement à la batterie

    Efficiency and Sustainability of the Distributed Renewable Hybrid Power Systems Based on the Energy Internet, Blockchain Technology and Smart Contracts-Volume II

    Get PDF
    The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems, and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications, such as hybrid and microgrid power systems based on the Energy Internet, Blockchain technology, and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above

    New players in intelligent transportation: Autonomous Segway in a dynamic environment

    Get PDF
    This paper heralds a mathematical treatment of Segways as autonomous robots for personal transportation and deliveries and courier services in constrained dynamic environments from a bird’s-eye view. New velocity-based stabilizing controllers of an autonomous nonholonomic two-wheeled self-balancing personalized Segway robot are extracted from a total potential developed by employing the Lyapunov-based Control Scheme (LbCS) for navigation in a partially known environment. Velocity controllers’ cost and time effectiveness and efficiency result from the interaction of the three prominent pillars of LbCS: smoothest, shortest, and safest path for motion planning. Furthermore, the autonomous personal transporter has an obstacle avoidance sensor with a limited detection range ideal for fast navigation in dynamic environments with narrow corridors, tracks, and pathways. This also successfully facilitates navigation in a partially known environment where the sensors only receive and avoid static and dynamic obstacles in a limited range. The results are numerically validated, and the efficacy of the new controllers is exemplified via computer simulations, which illustrate the forward, backward, and zero-turn radius maneuvers of the Segway robot. Introducing the particular autonomous personal transporter would contribute to transportation systems of smart cities

    Formation control of autonomous vehicles with emotion assessment

    Get PDF
    Autonomous driving is a major state-of-the-art step that has the potential to transform the mobility of individuals and goods fundamentally. Most developed autonomous ground vehicles (AGVs) aim to sense the surroundings and control the vehicle autonomously with limited or no driver intervention. However, humans are a vital part of such vehicle operations. Therefore, an approach to understanding human emotions and creating trust between humans and machines is necessary. This thesis proposes a novel approach for multiple AGVs, consisting of a formation controller and human emotion assessment for autonomous driving and collaboration. As the interaction between multiple AGVs is essential, the performance of two multi-robot control algorithms is analysed, and a platoon formation controller is proposed. On the other hand, as the interaction between AGVs and humans is equally essential to create trust between humans and AGVs, the human emotion assessment method is proposed and used as feedback to make autonomous decisions for AGVs. A novel simulation platform is developed for navigating multiple AGVs and testing controllers to realise this concept. Further to this simulation tool, a method is proposed to assess human emotion using the affective dimension model and physiological signals such as an electrocardiogram (ECG) and photoplethysmography (PPG). The experiments are carried out to verify that humans' felt arousal and valence levels could be measured and translated to different emotions for autonomous driving operations. A per-subject-based classification accuracy is statistically significant and validates the proposed emotion assessment method. Also, a simulation is conducted to verify AGVs' velocity control effect of different emotions on driving tasks

    Operational research:methods and applications

    Get PDF
    Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order
    corecore