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检索条件"机构=Faculty of Control Systems and Robotics of ITMO University"

共 623 条记录，以下是141-150 订阅

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Development of a Mobile Reconfigurable Mecanum Robot with a Locking Device of Rollers

Development of a Mobile Reconfigurable Mecanum Robot with a ...

引用

IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Dmitrii N. Zakharov Andrei M. Iaremenko Denis M. Kurovskii Artem M. Kurovskii Oleg I. Borisov Botao Zhang Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia School of Automation Hangzhou Dianzi University Hangzhou China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper presents the design and analysis of an omnidirectional reconfigurable wheeled robot capable of switching between omnidirectional and conventional wheeled mode. We have developed a new pneumatic locking mechanism of rollers for the mecanum wheel. In the mecanum mode, the robot can perform holonomic movements, and in the wheeled platform mode, it can overcome inclined surfaces and perform more energy-efficient movements. In addition, the locking device allows the robot to brake faster compared to other mecanum robots. Unlike other works describing the reconfigurable structure of the mecanum wheel, this work offers a new design characterized by the simplicity of the mechanism and does not require the location of active reconfiguration elements inside the wheel itself. The paper describes the design concept and presents the mechanism for locking rollers. The study evaluates the use of the developed robot in various scenarios, including movement on an inclined surface, sudden braking on a plane and an inclined surface, and also analyzes the energy efficiency of the resulting solution for some operating scenarios. The experiments carried out confirm that this mobile platform, when switching mode, is able to move on surfaces with a large angle of inclination and perform more effective deceleration on both flat and inclined surfaces.

关键词： Performance evaluation Pressure sensors Regulators Wheels Switches Pneumatic systems Energy efficiency Mobile robots Brakes Robots

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Methods of Parts Digital Models Design for Problems Resolving in Technological Preparation of Production 10th

Methods of Parts Digital Models Design for Problems Resolvin...

引用

10th Conference on Modern Mechanical Engineering: Science and Education, MMESE 2021

作者： Pompeev, Kirill P. Timofeeva, Olga S. Yablochnikov, Eugeny I. Volosatova, Elena E. Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia CAD/CAM Technologies Bureau PAO «Techpribor» St. Petersburg Russia

ISBN: (纸本)9783030915520

The paper discusses issues of information integration of design and technological preparation of production (DPP and TPP). The role of suggested methods for constructing 3D models of parts is noted, based on the use of unified and standard constructive and technological elements (CTE) and directional formation of a 3D model of a part taking into account CTE structural levels. The use of these methods makes it easier to transform models in solving process tasks, including for constructing models of operational workpieces, calculation of technological dimensions, design of control programs (CP) for CNC machines and coordinate measurement machines (CMM). The suggested methods are most efficiently applied under the conditions of implementation into production of multioperational digital technological processes (TP). © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： 3D model of a part 3D model of an operational workpiece CNC machine Design preparation of production Digital model of a product Product life cycle Technological preparation of production Technological process Unified information space

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Analysis of the limiting behavior of a biological neurons system with delay 8

Analysis of the limiting behavior of a biological neurons sy...

引用

8th International School and Conference "Saint Petersburg OPEN 2021" on Optoelectronics, Photonics, Engineering and Nanostructures, SPbOPEN 2021

作者： Fedorov, E.G. Popov, I.Y. Faculty of Control Systems and Robotics ITMO University St. Petersburg197101 Russia

In this work an analytical and numerical analysis of the limiting behaviors of a system consisting of a pair of biological neurons was carried out. In this case connection between neurons will occur with a delay. As a neuron model, the FitzHugh-Nagumo model was chosen as a model that can reproduce many dynamic behaviors of a real neuron and, at the same time, is not very complex computationally. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Neurons

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Parameter Estimation of Autonomous Underwater Vehicles Dynamics. A Data-Driven Optimization Framework

Parameter Estimation of Autonomous Underwater Vehicles Dynam...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Radda Iureva Alexey Margun Egor Lykoyanov Faculty of Control Systems and Robotics ITMO Univresity Saint Petersburg Russia State Research Center of the Russian Federation Concern CSRI Elektropribor JSC ITMO University Saint Petersburg Russia

ISBN: (数字)9798331511241

ISBN: (纸本)9798331511258

Accurate parameter estimation in ship dynamics models is pivotal for enhancing navigation precision, optimizing control systems, and ensuring maritime safety. This study explores two distinct methodologies: the “Grey Box” approach, where the governing equations of ship dynamics are known but certain parameters remain unidentified, and the “Black Box” approach, which relies entirely on trajectory data without any prior knowledge of the underlying mathematical models. Leveraging machine learning techniques, specifically Long Short-Term Memory (LSTM) networks, alongside optimization algorithms like L-BFGS-B, this research aims to evaluate and compare the efficacy of both approaches in estimating model parameters and predicting ship trajectories. The findings demonstrate that while the Grey Box approach benefits from incorporating physical laws for parameter tuning, the Black Box method offers flexibility in modeling complex, nonlinear dynamics purely based on empirical data. The integrated use of these methodologies provides a robust framework for enhancing the accuracy and reliability of ship dynamics models, contributing significantly to maritime engineering applications.

关键词： Parameter estimation Accuracy Predictive models Prediction algorithms Mathematical models Trajectory Vehicle dynamics Marine vehicles Optimization Long short term memory

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Neural Network Approaches for Magnetization Surface Prediction in Switched Reluctance Motors: Classical, Radial Basis Function, and Physics-Informed Models 3

Neural Network Approaches for Magnetization Surface Predicti...

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3rd IEEE International Conference on Problems of Informatics, Electronics and Radio Engineering, PIERE 2024

作者： Demidova, Galina Bogdanov, Andrey Iaremenko, Andrei Xirong, Zhu Chen, Hao Anuchin, Alecksey Moscow Power Engineering Institute Electric Drive Department Moscow Russia Itmo University Faculty of Control System and Robotics Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining and Technology Xuzhou China

ISBN: (纸本)9798331516321

This paper investigates the prediction of magnetization surfaces in Switched Reluctance Motors using three distinct methods: classical Neural Networks, Radial Basis Function networks, and Physics-Informed Neural Networks. The study utilizes experimental data from a 7.5 kW SRM to assess the performance of these approaches, with all methods implemented in Python. Among the methods analyzed, PINN demonstrates the highest accuracy in predicting the magnetization surfaces, effectively capturing the underlying physical behavior of the motor. The computational costs of each method are evaluated, providing insights into training times, inference speeds, and floating-point operations per sample. The findings reveal that while NN offers a reasonable balance between performance and efficiency, the RBF method excels in training speed but shows limitations in capturing the physical dynamics of the system. In contrast, the PINN not only delivers superior predictive performance but also emphasizes the significance of incorporating physical principles into machine learning frameworks. The results highlight the applicability of these methods across various types of SRMs, suggesting their potential for enhancing control strategies in electrical and power engineering applications. © 2024 IEEE.

关键词： Radial basis function networks

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Adaptive Direct Compensation of External Disturbances for Mimo Linear systems

Adaptive Direct Compensation of External Disturbances for Mi...

引用

International Russian Automation Conference (RusAutoCon)

作者： Bui Van Huan Alexey A. Margun Artem S. Kremlev Department of Control Systems and Robotics ITMO University St. Petersburg Russia Department of Control Systems and Robotics IPME RAS ITMO University St. Petersburg Russia

The paper proposes a new algorithm for compensating external disturbances for a class of multi-input multi-output (MIMO) linear systems. The solution of the problem is based on the use of the internal model principle and the extended error adaptation algorithm. It is assumed that the disturbance is the output of an autonomous linear generator with unknown parameters. At the first stage, a full-order unknown input observer (UIO) is synthesized to solve the problem of estimating the state vector of the plant. Then a new observer of external disturbance is formed on the basis of state vector estimates. At the last stage, based on the new observer's estimates, a system with an extended state vector is formed for that a controller providing compensation of disturbance is constructed. The performance of the obtained results is confirmed using computer simulation in MATLAB Simulink.

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Algorithm for Detecting Surface Defects in Hot-Rolled Sheet Metal for Technical Vision systems

Algorithm for Detecting Surface Defects in Hot-Rolled Sheet ...

引用

Information, control, and Communication Technologies (ICCT), International Conference on

作者： Vyacheslav V. Konyashov Alexey S. Sergeev Alexey V. Fedorov Kseniya A. Konyashova Oleg A. Kolganov Faculty of Control Systems and Robotics ITMO University Saint Petersburg Russia Researcher Scientific and Technical Center “Etalon” Saint Petersburg Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The work presents the results of developing an algorithm for detecting surface defects in hot-rolled metal sheets for technical vision systems implementing the method of optical (laser) triangulation. The detection algorithm is implemented for a technical vision system based on a vision camera and a linear laser source. The results of experimental modeling are provided to determine the parameters of the optical detection scheme that meets the technological requirements of metal production. The experimental validation results of the detection algorithm for determining the sizes and locations of volumetric and planar surface defects are shown

关键词： Machine vision Surface emitting lasers Metals Process control Production Optical imaging Laser modes Laser transitions Laser applications Metal products

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Leader-Follower Tracking with Collision Avoidance for Omni-directional Mobile Robots:Linear vs Homogeneous controller

Leader-Follower Tracking with Collision Avoidance for Omni-d...

引用

第43届中国控制会议

作者： Wenbin Yuan Chunyun Dong Xuechao Duan Andrey Polyakov Konstantin Zimenko Xubin Ping School of Electro-Mechanical Engineering Xidian University Inria Lille Univ.LilleCNRS Faculty of Control Systems and Robotics ITMO University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper deals with the leader-follower tracking control for two omni-directional mobile robots,the controller of the leader omni-directional mobile robot is unknown and the safe region is given. A linear controller is firstly designed for the follower omni-directional mobile robot such that the asymptotical stability is guaranteed. Based on the linear controller,a homogeneous controller is obtained,and the error system is guaranteed to be stabilized in finite-time. Compared with the linear controller,the homogeneous controller has the properties of faster convergence and better robustness. Furthermore,the convergence rate of the homogeneous controller can be simply tuned by properly selecting the homogeneity degree. The simulation results are given to illustrate the effectiveness of the designed controllers.

关键词： Homogeneous System Leader-follower Tracking Omni-directional Mobile Robot Finite-Time control

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Research of the possibility of using a neural network in the signal filtering instead of adaptive filters*

Research of the possibility of using a neural network in the...

引用

International Conference on control, Decision and Information Technologies (CoDIT)

作者： Kirill A. Shabanov Sergey M. Vlasov Alexey A. Margun Dmitrii Dobriborsci Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Technology Campus Cham Deggendorf Institute of Technology Cham

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The article aims to research the application of neural networks in signal adaptive filtering. The problem of filtering signals from noise and distortion is relevant in control systems. In this paper, white noise filtering using adaptive filters and neural networks is reviewed. Neural network algorithms were chosen to solve the problem of signal filtering. Neural networks and classical adaptive filtering algorithms, such as the least mean squares and the recursive least squares, were compared considering their efficiency for additive white noise filtering tasks. A multi harmonic signal was filtered from the additive white Gaussian noise using these approaches. As a result, classical adaptive filtering algorithms demonstrated better performance in signal filtering tasks.

关键词： Adaptive systems Filtering Neural networks Adaptive filters Filtering algorithms Network architecture Harmonic analysis Distortion Information technology Power harmonic filters

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Modern Approaches for Equipment's Technical State Prediction

Modern Approaches for Equipment's Technical State Prediction

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Information, control, and Communication Technologies (ICCT), International Conference on

作者： Stepan Bratchikov Department of Control Systems and Robotics ITMO University Saint-Petersburg Russia

Any manufacturing process aims to become more efficient. There is a plenty ways to achieve this. One of those is industrial equipment technical state prediction. Some of the methods are considered. Also, inclusion of modern machine learning and digital twins techniques is reviewed. As a result, the method of describing a production process as set of separate operations characterized by the parameters of the equipment involved in order to predict the output quality of produced items is introduced.

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