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2022 International Conference Automatics and Informatics, ICAI 2022

作者： Mihalev, Georgi Yordanov, Stanimir Ormandzhiev, Krasimir Kostov, Krasen Mitev, Veselin Technical University of Gabrovo Department Automation Information and Control Technology Gabrovo Bulgaria Technical University of Gabrovo Department of Power Engineering Gabrovo Bulgaria

ISBN: (数字)9781665476256

ISBN: (纸本)9781665476256

An attempt to synthesize a robust control of an electro-hydraulic tracking system is discussed in the paper. Object nonlinearity is represented by an equivalent linear model in a state space with structured uncertainty. Some of the imprecisely known parameters are introduced as sources of structured uncertainty. An H∞ synthesis of a regulator has been attempted and simulation experiments have been carried out with the nonlinear model. The results of the simulation of the system with the proposed robust controller are compared with the data obtained when controlling the real system with a built-in PI controller. Transient analysis shows improved performance and stability in the operation of the electro-hydraulic system compared to that with PI control under the same operating conditions. © 2022 IEEE.

关键词： Robust control

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Design and control of a Magnetic-Wheeled Climbing Robot for Vertical Steel Surfaces: Motor Positioning Performance Through Model Reference Adaptive control

Design and Control of a Magnetic-Wheeled Climbing Robot for ...

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International Carpathian control Conference (ICCC)

作者： Claudia Fernanda Yaşar Buse Tacal Ucun Levent Ucun Department of Control and Automation Engineering Yildiz Technical University Istanbul Türkiye

ISBN: (数字)9798350350708

ISBN: (纸本)9798350350715

Climbing robots capable of performing activities on vertical steel walls are frequently utilized in the maintenance of high-rise structures and unsafe situations for human workers, including bridges, ships, liquid tanks, chimneys, pipelines, nuclear facilities, and wind turbines. A climbing robot outfitted with the necessary equipment performs activities such as monitoring, cleaning, search and rescue, and more. The fundamental aim is to design a sturdy and safe robotic system with an adhesion-to-the-wall approach that can move on the surface while carrying the essential sensing system, actuation, and drive system as power cables or suppliers. The principal restrictions are the large forces that appear in the system and directly affect the motors. This paper presents a climbing robot design with magnetic wheels powered by a direct current motor; a simplified model with experimental parameter identification is utilized, and a model incorporating all forces is used to develop and test a model reference adaptive controller. Coulomb friction, magnetic forces that hold the system to the wall, and the gravity force are defined as the parts of the overall disturbance. A well-designed motion controller must be accurate enough to drive the robot's trajectory while also being robust enough to withstand overall disturbances. It must also take into account the limited control signal and saturation related with the servomotors. MATLAB/Simulink is used to identify experimental parameters and simulate various control scenarios.

关键词： Adaptation models Parameter estimation Wheels Climbing robots Robot sensing systems Mathematical models Steel

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Stage-cost design for optimal and model predictive control of linear port-Hamiltonian systems: Energy efficiency and robustness

Stage-cost design for optimal and model predictive control o...

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93rd Annual Meeting of the International Association of Applied Mathematics and Mechanics, GAMM 2023

作者： Şen, Gökçen Devlet Schaller, Manuel Worthmann, Karl Optimization-based Control Group Institute of Mathematics Technische Universität Ilmenau Ilmenau Germany Department of Control and Automation Engineering Istanbul Technical University Istanbul Turkey

We consider singular optimal control of port-Hamiltonian systems with minimal energy supply. We investigate the robustness of different stage-cost designs w.r.t. time discretization and show that alternative formulations that are equivalent in continuous time, differ strongly in view of discretization. Furthermore, we consider the impact of additional quadratic control regularization and demonstrate that this leads to a considerable increase in energy consumption. Then, we extend our results to the tracking problem within model predictive control and show that the intrinsic but singular choice of the cost functional as the supplied energy leads to a substantial improvement of the closed-loop performance. © 2023 The Authors. Proceedings in Applied Mathematics & Mechanics published by Wiley-VCH GmbH.

关键词： Model predictive control

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Extended Kalman Filter Based Nonlinear Probabilistic Model Predictive control of an Autonomous Motorcycle

Extended Kalman Filter Based Nonlinear Probabilistic Model P...

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International Conf on Electrical and Electronic engineering (ICEEE)

作者： Nurettin Çerçi Yaprak Yalçin Mechatronics Engineering Department Istanbul Technical University Istanbul Turkey Control and Automation Engineering Department Istanbul Technical University Istanbul Turkey

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

This work focuses on the control of a nonlinear autonomous motorcycle model using Probabilistic Model Predictive control (MPC). The main purpose of this work is to control the speed, yaw angle and roll angle of the motorcycle while keeping its balance during a maneuver. The Probabilistic MPC takes into account the probabilistic disturbances acting on the control inputs or the state variables. The cost function of the optimization of this proposed nonlinear probabilistic MPC is different than the cost of traditional deterministic MPC, such that, it contains terms that represent the mean of the state variable which is calculated with the help of an Extended Kalman Filter (EKF) and also the terms as the functions of covariances of the state variables and control inputs. The optimization algorithm is fed with these mean and covariance values every time instant, then the controller calculates the optimal control sequence to apply it to the system model. The speed of the motorcycle, the yaw angle and, the roll angle of the motorcycle are controlled with good efficiency.

关键词： Costs Motorcycles Optimal control Predictive models Probabilistic logic Cost function Kalman filters Predictive control

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Developing Digital Twin for Electromechanical System of Rolling Stand in Simulink Real Time

Developing Digital Twin for Electromechanical System of Roll...

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2024 International Ural Conference on Electrical Power engineering, UralCon 2024

作者： Radionov, Andrey A. Karandaev, Alexandr S. Loginov, Boris M. Khramshin, Vadim R. Moscow Polytechnic University Department of Automation and Control Moscow Russia Magnitogorsk Iron and Steel Works Magnitogorsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia

ISBN: (纸本)9798350386028

The development of digital twins (DTs) of industrial electrical systems is attributed to the need for the reduction of time and material resource inputs during their virtual commissioning (VC). The same problem occurs during renovation with complete or partial equipment replacement and/or control systems. These problems can be efficiently solved by developing object-oriented DTs based on the Simulink Real Time software and using hardware-in-the-loop simulation (HIL). This software is compatible with Matlab Simulink and the Simscape package, which makes it suitable for the industrial usage. The authors suggest a HIL-based approach that helps make a virtual real-time computer model, with process control signals coming from the industrial PLC that controls the real physical object. This problem occurred during the renovation of the horizontal stand electric drives of a 5000 plate mill. The authors provide the flow charts of the electromechanical system and the object-oriented DT. The implementation of DT in Matlab Simulink Desktop Real Time is reviewed in laboratory settings. The authors present the block structures that make up a virtual model of the electromechanical system. The developed DT was used to adjust control algorithms and controllers and study the dynamic modes over a rolling cycle. The adequacy of the processes was tested by comparing the oscillograms obtained with the developed DT and the rolling mill. The authors stress the feasibility of developing DTs on the Simulink Real Time platform using HIL simulation during VC and renovation of complex industrial objects. © 2024 IEEE.

关键词： MATLAB

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Self-Supervised Learning with Min-Max Distance Approach for Few-Shot Steel Surface Defects Recognition 43

Self-Supervised Learning with Min-Max Distance Approach for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Tianlei Chen, Xinyao Li, Zeliang Zhou, Zhencai Zhou, Zhiheng Wuyi University School of Electronic and Information Engineering Jiangmen China Jiangmen Key Laboratory of Kejie Semiconductor Bonding Technology and Control System Jiangmen China Wuyi University School of Mechanical and Automation Engineering Jiangmen China Guangdong Province Kejie Machinery Automation Company Technical Department Jiangmen China

ISBN: (纸本)9789887581581

Surface defects in steel are crucial for quality inspection in the manufacturing of industrial metal products. While deep learning methods have been extensively studied in this field, the lack of large-scale annotated defect samples imposes significant labeling pressure, making training fully supervised deep models challenging. In response to this issue, we employ self-supervised learning for few-shot recognition, effectively learning representations from limited unlabeled data and achieving defect recognition with a small amount of labeled samples. In particular, we construct Other encoder with multi-view information and Base encoder with single view information based on the distillation self-supervised learning framework through the multi-crops mechanism, and the Other encoders and Base encoders perform information share. Our main contribution is that, based on this framework, we propose a new regularization method to solve the problem of instances deviating from the center of self-supervised clustering by minimizing the maximum instance distance (MMD). In testing, fine-tuning the MMD pre-trained model with a small number of labeled data achieves superior recognition performance on the steel surface defect dataset NEU, significantly outperforming other testing methods. © 2024 technical Committee on control Theory, Chinese Association of automation.

关键词： Self-supervised learning

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Acoustic Positioning of Partial Discharges in High-Voltage Transformer Tank

Acoustic Positioning of Partial Discharges in High-Voltage T...

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2024 International Ural Conference on Electrical Power engineering, UralCon 2024

作者： Karandaev, Alexandr S. Loginov, Andrey B. Nikolaev, Andrey A. Moscow Polytechnic University Department of Automation and Control Moscow Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia Magnitogorsk Iron and Steel Works Magnitogorsk Russia

ISBN: (纸本)9798350386028

This report reviews an example of acoustic positioning of partial discharges (PD) in the tank of a high-voltage oil-filled transformer. The literature review confirms the importance of PD monitoring and justifies the feasibility of positioning discharge activity centers. The precise positioning of PD sources is required to determine the location of insulation defects. The authors provide brief information on the development of PD positioning methods and note that their practical application has been insufficiently covered in publications. They present the results of electromagnetic and acoustic PD positioning in a 110 kV transformer. Some details are provided on the devices and measurement methods used, including the localization of areas with increased PD intensity using one acoustic sensor and the subsequent center localization through the installation of 4 sensors at even intervals. The authors provide PD signals and defect impulses received from each of the sensors and demonstrate the difference in the registration time of these signals. They explain the principle behind PD center positioning, which is determined considering delays in signal reception. The authors demonstrate the usage of the Inva (Portable) software for the processing and visualization of acoustic positioning results. They note that changes in the propagation rate of acoustic waves in a heterogeneous medium result in the reduced accuracy of results. The authors also outline the prospects of the research into the elimination of occurring defects. © 2024 IEEE.

关键词： Oil filled transformers

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Validation of Delayed Anesthesia Model Using Identification Methods and Correlation Analysis

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IFAC-PapersOnLine 2024年第27期58卷 172-177页

作者： Bora Ayvaz Erhan Yumuk Clara M. Ionescu Ali Fuat Ergenç Control and Automation Engineering Department Istanbul Technical University Istanbul 34469 Turkey Department of Electromechanics System and Metal Engineering Ghent University 9052 Ghent Belgium

Many successful control strategies for anesthetic processes do not adequately consider time delays despite potential 30-second delays from biophase and bispectral index (BIS) monitoring. This study introduces linear delayed Pharmacokinetic-Pharmacodynamic (PK-PD) patient models that correlate more to real patient outputs than common non-delayed models. The delayed models are obtained for both effect-site concentration (Ce) and BIS outputs. The model structures are identified using autoregressive exogenous input (ARX) and delayed-ARX (DARX) polynomial models and least squares estimations (LSE) using the real surgical data of the open-access database VitalDB. Validation of delayed PK-PD patient models involves using correlation analysis. Results indicate that PK-PD patient models with output delays exhibit higher correlations with real patient data, particularly when considering BIS output.

关键词： Time Delay Models General Anesthesia System Identification Correlation Analysis Closed-Loop control

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Signal Processing for Acoustic Emission Signature Analysis and Defect Detection 26

Signal Processing for Acoustic Emission Signature Analysis a...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Altay, Yeldos A. Kuzivanov, Dmitry O. Altay, Dinara A. Fedorov, Alexey V. Satbayev University Department of Robotics and Technical Means of Automation Almaty Kazakhstan ITMO University Faculty of Control Systems and Robotics Saint-Petersburg Russia Military Engineering Institute of Radio Electronics and Communications Department of Natural Sciences Almaty Kazakhstan

ISBN: (纸本)9798350361728

This article presents the results of implementing a digital signal processing method for analyzing the acoustic emission (AE) signature and detecting defects such as cracks and pores. The signal processing method is based on a cascade connection of digital high-pass filters and ensures the selection of informative signals and increases the signal-to-interference ratio. In order to control the formation of defects in the process of selective laser melting, the paper presents the results of experimental testing of the cascade filtration method for detecting defects in the internal structure such as cracks and pores. The signal components recorded during the development of defects during the growth of additive manufacturing products were extracted. AE signatures were analyzed and statistical relationships were assessed. The relationship between the parameters of the AE signal and the values of laser radiation power has been identified, which characterizes the process of defect formation. © 2024 IEEE.

关键词： High pass filters

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Empowering Lab Education: Integrating a Vision-Based Monitoring System with Small-Scale Self-Driving Experiment Platforms

Empowering Lab Education: Integrating a Vision-Based Monitor...

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IEEE/SICE International Symposium on System Integration

作者： Junru Ren Nis Fisker-Bødker Ronja Güldenring Jin Hyun Chang Tejs Vegge Ole Ravn Lazaros Nalpantidis Department of Electrical and Photonics Engineering Automation and Control Group Technical University of Denmark Department of Energy Conversion and Storage Technical University of Denmark

ISBN: (数字)9798331531614

ISBN: (纸本)9798331531621

The rise of self-driving laboratories has seen significant growth across various research domains, particularly in chemistry, materials science and life science. However, a major challenge persists—the majority of self-driving systems are costly due to the use of highly precise lab equipment, robotic platforms, and case-specific algorithms, rendering these systems less accessible for educational purposes. This paper takes a multidisciplinary approach; we first introduce a small-scale self-driving experiment platform tailored for educational use, focusing on liquid materials mixing tasks commonly seen in chemistry and life sciences. To understand the operational status in real-time while maintaining self-driving capability and efficiency, we propose a novel system concept: employing a mobile robot as the lab supervisor to monitor the experiment process across multiple identical self-driving platforms. Specifically, this paper focuses on implementing a vision-based monitoring system. A deep learning architecture with a new training strategy is presented to jointly address two tasks: (a) vessel and content material segmentation and (b) volume estimation. The two tasks can be trained independently but can be inferred end-to-end by integrating them into the Mask R-CNN framework. Through evaluating the monitoring module on a real dataset, the results showcase promising detection capabilities, good real-time performance, and compatibility with the self-driving platform, indicating the feasibility of our proposed system.

关键词： Training Materials science and technology Chemistry Volume measurement System integration Rendering (computer graphics) Real-time systems Life sciences Mobile robots Monitoring

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