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Distributed formation control of networked mechanical systems

IFAC-PapersOnLine 2022年第13期55卷 294-299页

作者： N. Javanmardi P. Borja M.J. Yazdanpanah J.M.A. Scherpen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Cognitive Robotics Delft University of Technology Delft The Netherlands Jan C. Wilems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Groningen The Netherlands

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach.

关键词： Autonomous systems Cooperative control Networked control systems Large-scale systems Port-Hamiltonian systems Scalability

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A Hybrid NOMA-PLNC Wireless Relay Scheme

A Hybrid NOMA-PLNC Wireless Relay Scheme

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Samikkannu Rajkumar Dushantha Nalin K. Jayakody Zheng Chang School of Computer Science and Robotics National Research Tomsk Polytechnic University Tomsk Russia Faculty of Information Technology University of Jyvaskykä Jyvskylä Finland

ISBN: (数字)9781728197944

ISBN: (纸本)9781728197951

In this paper, a novel system model for the non orthogonal multiple access (NOMA) based wireless network is proposed using physical layer network coding (PLNC) scheme. The outage performance of a two pairs hybrid NOMA-PLNC relay network is analyzed. Proposed network is designed with three time slots and half-duplex decode-and-forward (DF) relay. A closed form expression for the end-to-end outage probability of the proposed NOMA-PLNC relay network is derived. It is noted that the performance of the proposed hybrid NOMA-PLNC relay network is significantly improved when compare to the conventional orthogonal multiple access (OMA)-PLNC relay network. Finally, numerical results of the proposed relay network is validated using the simulated experimental results.

关键词： NOMA Closed-form solutions Wireless networks Relay networks (telecommunication) Probability Physical layer Power system reliability

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Adaptive Non-Maximum Suppression to Improve Performance of Rumex Detection

SSRN

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SSRN 2022年

作者： Al-Badri, Ahmed Husham Ismail, Nor Azman Al-Dulaimi, Khamael Salman, Ghalib Ahmed Salam, Md Sah Bin Haji Al-Sabaawi, Aiman School of Computing Faculty of Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Computer Science Department College of Science Al-Nahrain University Baghdad Iraq School of Electrical Engineering and Robotics Queensland University of Technology BrisbaneQLD4000 Australia Department of Computer Science Middle Technical University Baghdad Iraq School of Computer Science Queensland University of Technology BrisbaneQLD4000 Australia

Weed detection methods based on Region-Convolutional Neural Network (R-CNN) frameworks still suffer from a lack of detection rate due to overlapping and occlusion leaves issues. This paper presents an Ensemble-Region Convolutional Neural Networks (E-RCNN) model of three state-of-the-art networks to detect Rumex obtusifolius L. ( R. obtu .) weeds under various condition especially overlapping. The proposed E-RCNN model is used due to its novelty of using ensemble classifiers with the combination of three extractors at its backbone. The Adaptive Non-Maximum Suppression (ANMS) is proposed with the Region Proposal Network (RPN) to enhance the detection performance of overlapping and occluded objects by overcoming the drawbacks of the conventional Non-Maximum Suppression (NMS). Three main stages are proposed as a framework to achieve the classification and detection goals, including pre-processing stage, classification stage, and detection stage. A hybrid model of three CNN extractor networks is used as the backbone in the classification stage. Thus, integrating three networks into one robust model increases the recognition capability by extracting additional useful features more efficiently than those from an individual network. For detection, RPN is used to generate multi-proposed boxes, whereas ANMS is used to select the best box that has a high score rate to match the target object. Our proposed model has trained and tested two standard benchmarking datasets of Rumex weeds under real-world data. The proposed model tested each dataset separately to evaluate the detection rate in terms of Intersection over Union (IoU). To evaluate the detection rate, AlexNet, Single-Shot Detector (SSD), DetectNet and Faster R-CNN with conventional NMS models are used to compare the results. The evaluation performances of AlexNet, SSD, DetectNet, and Faster R-CNN on the IoU metric are 0.81, 0.83, 0.84, and 0.88, respectively. The proposed model achieves the highest score in localization

关键词： Convolutional neural networks

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Mutual Impacts of Different Dead-times and Control Sample Times on SiC Inverter Loss in Experimental Motor Drive at High Carrier Frequencies

Mutual Impacts of Different Dead-times and Control Sample Ti...

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International Conference on Communications and Electronics, ICCE

作者： Nguyen Gia Minh Thao Van-Long Pham Kutsukake Asuka Keisuke Fujisaki Ton Duc Do Department of Mechanical Electrical and Electronic Engineering Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Department of Automation School of Electrical and Electronic Engineering Hanoi University of Science and Technology Hanoi Vietnam Next Generation Tatara Co-Creation Centre Shimane University Matsue Japan Electromagnetic Energy System Laboratory Toyota Technological Institute Nagoya Japan Department of Robotics and Mechatronics School of Engineering and Digital Sciences Nazarbayev University Astana Kazakhstan

ISBN: (数字)9798350379792

ISBN: (纸本)9798350379808

At high pulse-width modulation (PWM) carrier frequencies up to 200 kHz using silicon carbide (SiC) devices, the individual and mutual impacts of the sample time and dead-time on the SiC inverter loss in a motor drive system may become significantly. Thus, these issues under load condition are experimentally investigated and analyzed in the present study, where the dead-time is from 250 to 1000 ns and the control sample time is from 100 to 1000 μs. Furthermore, the measured results with the SiC metal–oxide-semiconductor field-effect transistor (MOSFET) inverter are briefly compared to that with the silicon (Si) insulated-gate bipolar transistor (IGBT) inverter for reference. Moreover, the total harmonics distortion (THD) of the measured voltage and current of the considered interior permanent magnet synchronous motor (IPMSM) is provided to explain the results. Finally, insights with theoretical analysis are shown as complementary explanations of the experimental findings. The outcome of this research can be treated as a reference in choosing the suitable value of the control sample time for IPMSM drive systems using SiC-MOSFET inverters.

关键词： Semiconductor device measurement Time-frequency analysis Motor drives Voltage measurement Magnetic field measurement Silicon carbide Current measurement

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Lateralized Learning for Multi-Class Visual Classification Tasks

arXiv

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arXiv 2023年

作者： Siddique, Abubakar Browne, Will N. Grimshaw, Gina M. The School of Engineering and Computer Science Victoria University of Wellington PO Box 600 Wellington6140 New Zealand The Faculty of Engineering School of Electrical Engineering & Robotics Queensland University of Technology Brisbane4000 Australia The Cognitive the School of Psychology Victoria University of Wellington PO Box 600 Wellington6140 New Zealand

The majority of computer vision algorithms fail to find higher-order (abstract) patterns in an image so are not robust against adversarial attacks, unlike human lateralized vision. Deep learning considers each input pixel in a homogeneous manner such that different parts of a "locality-sensitive hashing table" are often not connected, meaning higher-order patterns are not discovered. Hence these systems are not robust against noisy, irrelevant, and redundant data, resulting in the wrong prediction being made with high confidence. Conversely, vertebrate brains afford heterogeneous knowledge representation through lateralization, enabling modular learning at different levels of abstraction. This work aims to verify the effectiveness, scalability, and robustness of a lateralized approach to real-world problems that contain noisy, irrelevant, and redundant data. The experimental results of multi-class (200 classes) image classification show that the novel system effectively learns knowledge representation at multiple levels of abstraction making it more robust than other state-of-the-art techniques. Crucially, the novel lateralized system outperformed all the state-of-the-art deep learning-based systems for the classification of normal and adversarial images by 19.05% − 41.02% and 1.36% − 49.22%, respectively. Findings demonstrate the value of heterogeneous and lateralized learning for computer vision applications. Copyright © 2023, The Authors. All rights reserved.

关键词： Image classification

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Modular smart furniture system for independent living of older adults- user experience study

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Gerontechnology 2020年第4期19卷 1-13页

作者： Merilampi, Sari Poberžnik, Anja Saari, Santeri Serrano, J. Artur Güttler, Jörg Langosch, Katharina Bock, Thomas Zou, Ling Magne, Trine A. Faculty of Technology Satakunta University of Applied Sciences Pori Finland Department of Neuromedicine and Movement Science Faculty of Medicine and Health Sciences NTNU/Norwegian University of Science and Technology Trondheim Norway Chair of Building Realization and Robotics Technical University of Munich Munich Germany School of Microelectronics and Control Engineering Changzhou University Changzhou 213164 China

Background: The ageing of the population represents a significant challenge, however, it is also a huge potential driver for innovation. technology development capabilities are rapidly increasing, which enables new, innovative solutions when considering the ageing population. Objective: To promote the successful development and implementation of new technologies (in this case, smart furniture), positive user feedback and experiences are required. Methods: In this study, several modular smart furniture prototypes were developed, offering a potential solution to several challenges associated with ageing. The aim was to investigate which features positively affect user experience and consequently form the basis for smart, ageing-friendly furniture design guidelines. The smart furniture systems consisted of five prototypes: Fall Detection system with assistive Mobile Robot, ReAbleChair, Magic Mirror, Smart Gaming Chair, and 3D printed handles. These prototypes were presented to seniors in a home-like environment, after which participants completed a questionnaire and were interviewed. The themes used in the semi-structured interview followed the structure of Jesse Garrett's user experience framework. Results: The most essential feature was found to be modularity, or the ability to customize solutions according to the end user's capabilities and needs. In addition, results highlight that smart furniture should be aesthetically pleasing whilst still serving its primary purpose (i.e. as an item of furniture). Administrative components of the software should be removed from the end user's User Interface (UI) and integrated in a separate UI, to simplify the end user's interaction with the technology. Installation and customization services, as well as value-adding services (i.e. monitoring) were seen to offer potential. Conclusions: In general, the user experiences were positive. Smart features were readily accepted as part of the furniture prototypes, with hidden technologi

关键词： active and assistive living assistive technologies design for older adults fall detection serious games Smart furniture

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Automated Leukemia Screening and Sub-types Classification Using Deep Learning

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Computer Systems science & Engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

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Numerical procedure for optimal control of hybrid systems with sliding modes, Part I

arXiv

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arXiv 2021年

作者： Pytlak, Radoslaw Suski, Damian Faculty of Mathematics and Information Science Warsaw University of Technology Warsaw00-665 Poland Institute of Automatic Control and Robotics Warsaw University of Technology Warsaw02-525 Poland

This paper concerns the numerical procedure for solving hybrid optimal control problems with sliding modes. The proposed procedure has several features which distinguishes it from the other procedures for the problem. First of all a sliding mode is coped with differential-algebraic equations (DAEs) and that guarantees accurate tracking of the sliding motion surface. The second important feature is the calculation of cost and constraints functions gradients with the help of adjoint equations. The adjoint equations presented in the paper take into account sliding motion and exhibit jump conditions at transition instants. The procedure uses the discretization of system equations by Radau IIA Runge–Kutta scheme and the evaluation of optimization functions gradients with the help of the adjoint equations stated for discretized system equations. In the first part of the paper we demonstrate the correspondence between the discrete adjoint equations and the discretized version of the continuous adjoint equations in the case of system equations described by ODEs. We show that the discrete adjoint state trajectories converge to their continuous counterparts in the case of ODEs. © 2021, CC BY.

关键词： Optimal control systems

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Application of Machine Learning to Performance Assessment for a class of PID-based Control Systems

arXiv

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arXiv 2021年

作者： Grelewicz, Patryk Khuat, Thanh Tung Czeczot, Jacek Nowak, Pawel Klopot, Tomasz Gabrys, Bogdan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Automatic Control and Robotics Gliwice44100 Poland University of Technology Sydney Faculty of Engineering and IT Advanced Analytics Institute NSW2007 Australia

In this paper, a novel machine learning derived control performance assessment (CPA) classification system is proposed. It is dedicated for a wide class of PID-based control industrial loops with processes exhibiting dynamical properties close to second order plus delay time (SOPDT). The proposed concept is very general and easy to configure to distinguish between acceptable and poor closed loop performance. This approach allows for determining the best (but also robust and practically achievable) closed loop performance based on very popular and intuitive closed loop quality factors. Training set can be automatically derived off-line using a number of different, diverse control performance indices (CPIs) used as discriminative features of the assessed control system. The proposed extended set of CPIs is discussed with comprehensive performance assessment of different machine learning based classification methods and practical application of the suggested solution. As a result, a general-purpose CPA system is derived that can be immediately applied in practice without any preliminary or additional learning stage during normal closed loop operation. It is verified by practical application to assess the control system for a laboratory heat exchange and distribution *** Codes 93 © 2021, CC BY-NC-SA.

关键词： Three term control systems

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First impressions of a humanoid social robot with natural language capabilities

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Scientific Reports 2025年第1期15卷 1-10页

作者： Herath, Damith Busby Grant, Janie Rodriguez, Adrian Davis, Jenny L. Collaborative Robotics Lab Faculty of Science and Technology University of Canberra Canberra Australia Collaborative Robotics Lab Faculty of Health University of Canberra Canberra Australia Department of Sociology The Australian National University Canberra Australia Department of Sociology Vanderbilt University Nashville United States

Concurrent developments in robotic design and natural language processing (NLP) have enabled the production of humanoid chatbots that can operate in commercial and community settings. Though still novel, the presence of physically embodied social robots is growing and will soon be commonplace. Our study is set at this point of emergence, investigating people’s first impressions of a humanoid chatbot in a public venue. Specifically, we introduced “Pepper” to attendees at an innovation festival. Pepper is a humanoid robot outfitted with ChatGPT. Attendees engaged with Pepper in a bounded interaction and provided feedback about their experience (n = 88). Qualitative analyses reveal participants’ mixed emotional resonance, reactions to Pepper’s embodied form and movements, expectations about interpersonal connection and rituals of interaction, and attentiveness to issues of diversity and social inclusion. Findings document live responses to a humanoid chatbot, highlight the affective, social, and material forces that shape human–robot interaction, and underscore the value of “in the wild” studies, creating space and scope for user-publics to express their perspectives and concerns. Such insights are acutely relevant as we enter this next era of social robotics. © The Author(s) 2025.

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