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11th IEEE International Conference on System engineering and Technology, ICSET 2021

作者： Sadiq, Musaab Esam Humaidi, Amjad Jaleel Kadhim, Saleem Khalefa Mhdawi, Ammar Al Alkhayyat, Ahmed Ibraheem, Ibraheem Kasim General Company for Grain Processing Ministry of Trade Baghdad Iraq University of Technology Control and Systems Eng. Dept. Baghdad Iraq Edge Hill University Department of Computer Science United Kingdom College of Technical Engineering Islamic University Najaf Iraq College of Engineering University of Baghdad Baghdad Iraq

ISBN: (纸本)9781665437660

The manipulators actuated by Pneumatic Artificial Muscles (PAMs) are characterized by high nonlinearity and time varying of their coefficients. Therefore, nonlinear and robust controllers are required to cope with these challenging control problems. This work presents the development of control design for trajectory tracking of PAM-Actuated manipulator based on Sliding Mode control (SMC). The PSO technique is used to tune the design parameters of proposed controller for further enhancement of controlled PAM system performance. A comparison study has been conducted between the optimal and non-optimal SMC controllers via computer simulation using MATLAB programming software. © 2021 IEEE.

关键词： Trajectory tracking System performance Programming Muscles Manipulators Systems engineering and theory Numerical simulation

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Recent advances in data-driven methods for degradation modelling across applications

arXiv

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arXiv 2025年

作者： Jarosz, Anna Zagorowska, Marta Baranowski, Jerzy AGH University of Krakow Dept. of Automatic Control & Robotics al. Mickiewicza 30 Krakow30-059 Poland NTNU Department of Engineering Cybernetics Trondheim7034 Norway

Understanding degradation is crucial for ensuring the longevity and performance of materials, systems, and organisms. To illustrate the similarities across applications, this article provides a review of data-based method in materials science, engineering, and medicine. The methods analyzed in this paper include regression analysis, factor analysis, cluster analysis, Markov Chain Monte Carlo, Bayesian statistics, hidden Markov models, nonparametric Bayesian modeling of time series, supervised learning, and deep learning. The review provides an overview of degradation models, referencing books and methods, and includes detailed tables highlighting the applications and insights offered in medicine, power engineering, and material science. It also discusses the classification of methods, emphasizing statistical inference, dynamic prediction, machine learning, and hybrid modeling techniques. Overall, this review enhances understanding of degradation modelling across diverse domains. © 2025, CC BY-SA.

关键词： Hybrid materials

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On the impact of edge modifications for networked control systems ⁎

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IFAC-PapersOnLine 2020年第2期53卷 10969-10974页

作者： Gustav Lindmark Claudio Altafini Division of Automatic Control Dept. of Electrical Engineering Linköping University SE-58183 Linköping Sweden

This paper investigates the impact of addition/removal of edges in complex networks. Growing a network by the addition of edges has for instance been suggested as a way to improve network robustness to external disturbances. Moreover, when network controllability is considered, designing edge additions is a promising alternative to add more actuation capabilities in order to improve different performance metrics. We quantify the impact of an edge modification with the H ∞ and H 2 norms. For networks with positive edge weights we show how the H ∞ norm can be computed exactly for each possible single edge modification, while for the H 2 norm we instead obtain a lower bound. This bound is linked to the trace of the controllability Gramian, hence it can be used for instance to reduce the energy needed for control.

关键词： Complex networks Network topology design controllability Positive systems

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Comparative Study of Optimal Nonlinear control Schemes for Hanging Mass Actuated by Uncertain Pneumatic Muscle

Comparative Study of Optimal Nonlinear Control Schemes for H...

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11th IEEE International Conference on System engineering and Technology, ICSET 2021

作者： Sadiq, Musaab Esam Humaidi, Amjad Jaleel Kadhim, Saleem Khalefa Mahdi, Abdulkareem Sh. Alkhayyat, Ahmed Ibraheem, Ibraheem Kasim General Company for Grain Processing Ministry of Trade Baghdad Iraq University of Technology Control and Systems Eng. Dept. Baghdad Iraq School of Computer Science and Eng. Taylor's University Malaysia College of Technical Engineering Islamic University Najaf Iraq College of Engineering University of Baghdad Baghdad Iraq

ISBN: (纸本)9781665437660

The systems actuated by Pneumatic Artificial Muscles (PAMs) are characterized by high nonlinearity and time-varying of their coefficients. Therefore, nonlinear and robust controllers are required to cope with these challenging control problems. This work presents the development of new control design for trajectory tracking of PAM-Actuated manipulator based on Sliding Mode control (SMC), Backstepping Sliding Mode control (BSMC). The control laws of controlled PAM hanging mass based on SMC and BSMC have been developed according to Lyapunov stability analysis. Additionally, the PSO technique is used to tune the design parameters of proposed controllers for further enhancement of controlled PAM system performance. A comparison study has been conducted among the proposed controllers via computer simulation using MATLAB/Simulink programming software. © 2021 IEEE.

关键词： Trajectory tracking System performance Muscles Programming Systems engineering and theory Software Nonlinear dynamical systems

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Evaluation of Deep Training and Adapting Algorithms in Medical with De-Noising EEG

Evaluation of Deep Training and Adapting Algorithms in Medic...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Ali Hadi Abdulwahid Girija Rani Karetla KVB. Ganesh A Suresh Kumar K. Radha K. Shivakumar Control and Automation Engineering Department Engineering Technical College Southern Technical University Basra Iraq School of Computer Data and Mathematical Sciences Western Sydney University Australia KL Business School Koneru Lakshmaiah Education Foundation Guntur Andhra Pradesh India Department of CSE Graphic Era Deemed to be University Dept. of IT St. Martin's Engineering College Secunderabad Telangana India School of Computer Science and Artificial Intelligence SR University Warangal Telangana India

An electroencephalogram that was captured with electrodes placed can easily get contaminated with a variety of artifacts. Here is a comparative of various electroencephalogram (EEG) de-noising techniques. Three alternative techniques are used to eliminate five different kinds of noise, and also the outcomes are evaluated. These three methods are just the Least Mean Square (LMS) technique, the Connected Neural Network, and also the Recursive Least - square (RLS) adaptable algorithm (FCNN). Period charts of the actual EEG signal, the noise EEG signal, and thus the predicted EEG signal are used to display the results. RRMSE and signal- to-noise ratio were utilized to compare the effectiveness of the 3 de-noising strategies in this study. Investigating the model parameters in this case, we discover the FCNN forecasts a better outcome compared to the other two methods.

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Synchronizing sequences for verification of finite state machines

Synchronizing sequences for verification of finite state mac...

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2019 International Conference on Information and Telecommunication Technologies and Radio Electronics, UkrMiCo 2019

作者： Mroshnyk, Maryna Shkil, Olexander Kulak, Elvira Rakhlis, Dariia Pahomov, Yurii Mroshnyk, Anatolii Dept. Specialized Computer Systems Ukrainian State University of Railway Transport Kharkiv Ukraine Dept. Computer Engineering Design Kharkiv National University of Radio Electronics Kharkiv Ukraine Dept. Automation and Control in Technical Systems of the National Technical University Kharkov Polytechnic Institute Kharkiv Ukraine

ISBN: (纸本)9781728126920

The method of detection and localization of design errors in HDL-models of finite state machines with arbitrary output functions was proposed. The diagnostic experiment is carried out bypassing all arcs of the Mealy machine, starting from the initial vertex, including for machines of the "nonexclusive" class. To ensure the return of the machine with a possible design error in the initial state, it is suggested to use synchronizing sequences. Diagnostic experiments were performed in the Active-HDL design environment. © 2019 IEEE

关键词： Diagnistic experiment HDL State diagram State machine Tests Verification Waveform

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A novel explainable ECG classification with spatio-temporal transformers and hybrid loss optimization

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Biomedical Signal Processing and control 2025年 110卷

作者： Inam Abousaber Hany El-Ghaish Haitham F. Abdallah Dept. of Information Technology Faculty of Computers and Information Technology University of Tabuk Tabuk Saudi Arabia Dept. of Computer and Control Faculty of Engineering Tanta University 31526 Gharbiya Tanta Egypt Dept. of Electrical Engineering Higher Institute of Engineering and Technology Kafrelsheikh 33511 Egypt

This paper presents a novel deep learning framework for ECG arrhythmias detection, integrating Spatio-Temporal Adaptive Embedding (STAE) Transformers and Variational Autoencoders (VAEs) to improve classification accuracy and address class imbalance. Traditional ECG classification models struggle to capture long-range temporal dependencies and handle imbalanced datasets, leading to poor sensitivity for rare arrhythmias. The proposed system employs STAE Transformers to model intricate temporal and spatial relationships within ECG signals to overcome these challenges. At the same time, VAEs generate diverse and realistic ECG samples to enhance model generalization, particularly for underrepresented arrhythmias. Additionally, combining Focal Loss and Dice Loss, a Hybrid Loss Function further optimizes performance by focusing on hard-to-classify arrhythmias. The model is evaluated on the MIT-BIH Arrhythmias Database and PTB Diagnostic ECG Database using 5-fold cross-validation, achieving an accuracy of 99.56% and a macro F1-score of 95.40%, outperforming existing state-of-the-art methods, with a 3.5% improvement in sensitivity for rare arrhythmias. To ensure interpretability, SHapley Additive exPlanations (SHAP) and Gradient-weighted Class Activation Mapping (Grad-CAM) are utilized, highlighting the QRS complex and RR intervals as the most critical features and confirming that the model focuses on clinically relevant waveform regions. These results demonstrate the effectiveness of our approach in developing an accurate, interpretable, and robust deep learning system for ECG arrhythmias detection, paving the way for more reliable clinical decision support systems.

关键词： Electrocardiography

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Improving the Efficiency of a Multistage Evaporator Station for Sugar Production Using Neural Networks

Improving the Efficiency of a Multistage Evaporator Station ...

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International Conference on Modern Electrical and Energy Systems (MEES)

作者： Nataliia Zaiets Nataliia Lutska Lidiia Vlasenko det. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine

ISBN: (纸本)9798350346848

The paper shows the process of developing a model of multistage evaporator station of a sugar factory based on a neural network. The neural network predicts the main performance indicators of the multistage evaporator station, such as the concentration of syrup at the output of the evaporator and the amount of evaporated water at the station. Unlike existing solutions, forecasting is performed in real time based on a set of indicators of the automation system (temperatures, flow rates, levels, pressure, density in the apparatus) and industrial laboratory (concentration of solids at the inlet to the evaporation station). The proposed neural network model has an MLP structure with 27 inputs, 2 outputs and one hidden layer with 20 neurons and predicts these indicators with an error of less than 5%. This allows to increase the informative support of the operator-technologist on the quality indicators of the enterprise without additional load on the industrial laboratory and without additional cost automatic quality devices, as well as to perform timely adjustment of the technological mode of the department.

关键词： Productivity Soft sensors Predictive models Solids Sugar industry Data models Real-time systems

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Overcoming the Fear of the Dark: Occlusion-Aware Model-Predictive Planning for Automated Vehicles Using Risk Fields

arXiv

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arXiv 2023年

作者： van der Ploeg, Chris Nyberg, Truls Sánchez, José Manuel Gaspar Silvas, Emilia van de Wouw, Nathan Netherlands Organisation for Applied Scientific Research Integrated Vehicle Safety Group Helmond5700 AT Netherlands Eindhoven University of Technology Dynamics and Control Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands Eindhoven University of Technology Control Systems Technology Group Mechanical Engineering Dept. P.O. Box 513 Eindhoven5600 MB Netherlands KTH Royal Institute of Technology Division of Robotics Perception and Learning School of Electrical Engineering and Computer Science Stockholm100 44 Sweden Scania CV AB Södertälje151 87 Sweden

As vehicle automation advances, motion planning algorithms face escalating challenges in achieving safe and efficient navigation. Existing Advanced Driver Assistance Systems (ADAS) primarily focus on basic tasks, leaving unexpected scenarios for human intervention, which can be error-prone. Motion planning approaches for higher levels of automation in the state-of-the-art are primarily oriented toward the use of risk- or anti-collision constraints, using over-approximates of the shapes and sizes of other road users to prevent collisions. These methods however suffer from conservative behavior and the risk of infeasibility in high-risk initial conditions. In contrast, our work introduces a novel multi-objective trajectory generation approach. We propose an innovative method for constructing risk fields that accommodates diverse entity shapes and sizes, which allows us to also account for the presence of potentially occluded objects. This methodology is integrated into an occlusion-aware trajectory generator, enabling dynamic and safe maneuvering through intricate environments while anticipating (potentially hidden) road users and traveling along the infrastructure toward a specific goal. Through theoretical underpinnings and simulations, we validate the effectiveness of our approach. This paper bridges crucial gaps in motion planning for automated vehicles, offering a pathway toward safer and more adaptable autonomous navigation in complex urban contexts. Copyright © 2023, The Authors. All rights reserved.

关键词： Motion planning

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Client-server Mobile System for Diagnosis of Asynchronous Motors

Client-server Mobile System for Diagnosis of Asynchronous Mo...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Olha Chorna Petro Kurliak Victor Busher Oleksii Chornyi Valerii Tytiuk Iurii Zachepa Institute of Education and Science in Electrical Engineering and Information Technologies Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Department of Electrical power engineering electrical engineering and electromechanics Ivano-Frankivsk National Technical University of Oil and Gas Ivano-Frankivsk Ukraine Dept. of Electrical Engineering and Electronics National University “Odessa Maritime Academy” Odessa Ukraine Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Systems of Automatic Control and Electric Drive Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine

This paper presents client-server mobile system for diagnosis of asynchronous motors. The system is created as a mobile application for smartphones and tablets. The system provides processing of the measured values of the currents and voltages of the stator phases of the asynchronous motor. According to the processing results, the results of diagnostics and forecasting of the current state of asynchronous motors are calculated. The software runs on the Android OS. The main purpose is to predict the current state of AD, which has a parametric electromagnetic asymmetry of the stator phases.

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