In the current study to address the incompatibility issue of the Eulerian and Lagrangian frame at FSI problems, a novel physical approach is proposed. According to this approach, the motion of the Lagrangian frame is ...
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A research project to create an intelligent autonomous navigation system is being considered. The system is implemented on the basis of cognitive technologies and machine learning. The system makes a decision by analy...
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The paper describes the development and research of a system of adaptation to faults of manipulators of underwater robots. The following types of faults were considered: unknown additional load torques on the output s...
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Radar Polarimetry is a convenient and promising technique to obtain information about target scattering properties. In this paper, the hydrometeor shape and orientation variations under the dynamic phenomena influence...
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Computer vision is a rapidly developing field of human knowledge. Due to the fullness of images information visual sensors, unlike other types of sensors, theoretically can cover the entire amount of information neces...
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Computer vision is a rapidly developing field of human knowledge. Due to the fullness of images information visual sensors, unlike other types of sensors, theoretically can cover the entire amount of information necessary for autonomous driving, registration of traffic violations, in various medical tasks and so on. The requirements for computer vision specialists are growing every day. At the same time, it is advisable to train specialists in related fields the basics of computer vision. This paper provides an overview of the main points that should be taken into account during the education process in the field of object detection and tracking using computer vision algorithms.
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 ...
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.
The paper focuses on developing a finite-time approach for sensors fault detection and isolation in MIMO systems. The proposed solution utilizes the synthesis of a bank of unknown input observers, tailored specificall...
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ISBN:
(数字)9798350349818
ISBN:
(纸本)9798350349825
The paper focuses on developing a finite-time approach for sensors fault detection and isolation in MIMO systems. The proposed solution utilizes the synthesis of a bank of unknown input observers, tailored specifically for each of sensor. A significant advantage of this solution over existing methods is its applicability to plants with any arbitrary relative degree. The paper introduces a modification that ensures finite-time convergence using Kreisselmeier's scheme combined with the dynamic regressor extension and mixing method. This modification guarantees that the convergence of observer estimates—and thus the diagnostic results—occurs within a user-specified timeframe. Additionally, the implementation of filters and threshold settings is discussed to prevent false alarms caused by measurement noise. The effectiveness of the developed approach is validated through computer simulations, confirming its robust performance.
3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolu...
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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 ...
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.
The paper proposes new ontologies for describing and diagnosing malfunctions of subsystems of autonomous underwater vehicles (AUV) as a part of the development of a previously created approach to the intelligent diagn...
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