the error-based active disturbance rejection control (EADRC) structure is investigated to obtain precise tracking control of a mechanical system with one degree of freedom. We formally take into account the uncertaint...
the error-based active disturbance rejection control (EADRC) structure is investigated to obtain precise tracking control of a mechanical system with one degree of freedom. We formally take into account the uncertainty of the input gain, which affects the performance of the controller, and consider stability of the closed-loop system for the full-order and reduced-order extended-state observers (ESOs). Apart from theoretical analysis, we present experimental results, which confirm that the application of the reduction-order observer can improve control performance. We also investigate whether the explicit formulation of the feedforward in EADRC makes it possible to improve the tracking precision under real conditions.
6D pose estimation is the committed step of autonomous docking of underwater vehicles using executive guidance, and it is also an important research topic in recent years. this method provides RGB images and CAD model...
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Diagnosing faults in electric motors is crucial for various applications, from everyday devices to industrial machinery. Authors propose a method for identifying motor faults using acoustic signals, which are easy to ...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
Diagnosing faults in electric motors is crucial for various applications, from everyday devices to industrial machinery. Authors propose a method for identifying motor faults using acoustic signals, which are easy to capture with microphones. Proposed approach involves analyzing these signals using Functional Data Analysis (FDA), representing frequency patterns with B-splines and Bayesian Mixture Model as classifier. In this paper, there was developed a classifier to categorize five motor fault types based on these transformed signals. By focusing on frequencies up to 2500 Hz relevant to motor issues, authors aim to detect faults without needing complex equipment and greatly shorten computation time. this approach yields promising results.
the importance of security in the modern, dynamically changing world seems to be understood across the globe. Different types of organizations, both from the public and the private sector, are creating strategies and ...
the importance of security in the modern, dynamically changing world seems to be understood across the globe. Different types of organizations, both from the public and the private sector, are creating strategies and investing large amounts of funds to implement Physical Protection Systems (PPS) in order to protect their assets. It appears relatively obvious that assessment of the effectiveness of PPS is important and required. Moreover, the result of the assessment should be reliable and cover as much as possible current threats, including those that are coming from cyberspace. In this paper, we propose a new approach to evaluating PPS. Our proposition as a starting point is using well-known EASI (Estimate of Adversary Sequence Interruption) methodology but reinforced withmethods aiming to cover the cybersecurity of PPS considering all potential adversary paths.
this paper studies the effect of the size of a large scale robot network on the fractional order of the dynamics of the step response of the system. We show that, for a scale free network with certain parameter values...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
this paper studies the effect of the size of a large scale robot network on the fractional order of the dynamics of the step response of the system. We show that, for a scale free network with certain parameter values, as the number of robots increases the fractional order also increases up to certain size network, after which the order plateaus. In contrast, for a much more structured platoon network, the opposite happens. this paper presents those results and discusses some hypotheses attempting to resolve the apparent contradiction. We are interested in investigating the presence of fractional order dynamics in systems of this type because they are becoming increasingly common for large scale engineered systems. Very large scale systems can be difficult to design, analyze and control and understanding various approaches to determine effective and accurate reduced order models is important. A concise fractional order description of the dynamics offers insight into the nature of the system that may not otherwise be available through either the full, very large scale system dynamics or other types of reduced order models.
the article presents the current approach in artificial intelligence methods used in predictive maintenance for electrical motors. the study focuses on presenting data classification methods for fault detection and is...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
the article presents the current approach in artificial intelligence methods used in predictive maintenance for electrical motors. the study focuses on presenting data classification methods for fault detection and isolation using data from condition monitoring systems. We discuss the advantages and disadvantages of using machine learning methods like perceptron and Support Vector Machine (SVM) for fault classification problems. Our conclusion shows great interest in machine learning methods combined with condition monitoring systems. Our future research will focus on comparing SVM, perceptron networks, and other methods, such as K-nearest neighbors, withtheir possibility for implementation in embedded firmware systems.
Object detection in 3D is a crucial aspect in the context of autonomous vehicles and drones. However, prototyping detection algorithms is time-consuming and costly in terms of energy and environmental impact. To addre...
Object detection in 3D is a crucial aspect in the context of autonomous vehicles and drones. However, prototyping detection algorithms is time-consuming and costly in terms of energy and environmental impact. To address these challenges, one can check the effectiveness of different models by training on a subset of the original training set. In this paper, we present a comparison of three algorithms for selecting such a subset – random sampling, random per class sampling, and our proposed MONSPeC (Maximum Object Number Sampling per Class). We provide empirical evidence for the superior effectiveness of random per class sampling and MONSPeC over basic random sampling. By replacing random sampling with one of the more efficient algorithms, the results obtained on the subset are more likely to transfer to the results on the entire dataset. the code is available at: https://***/vision-agh/monspec.
In this paper, a control strategy based on a coupled Proportional and State-Dependent Riccati Equation (P-SDRE) controller, which ensures a quick stabilization for a given angular position of an unmanned aerial vehicl...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
In this paper, a control strategy based on a coupled Proportional and State-Dependent Riccati Equation (P-SDRE) controller, which ensures a quick stabilization for a given angular position of an unmanned aerial vehicle in three-dimensional space, is presented. the Hamilton-Jacobi-Bellman function and the Riccati differential equation are used to develop the solution of the SDRE algorithm. Properly defined weighting matrices in performance index allow quadrotor’s fast and precise positioning with optimal stabilization of angular speeds. Cruise control of unmanned aerial vehicle is modelled and simulated. In order to prove the effectiveness of the method, disturbances modelled as wind gusts are included in the simulation.
In this paper, a newly developed author’s vision system allowing identification of packages moving on the conveyor belt and their classification is presented. An important aspect is that the mentioned objects move at...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
In this paper, a newly developed author’s vision system allowing identification of packages moving on the conveyor belt and their classification is presented. An important aspect is that the mentioned objects move at relatively high speeds, which is challenging for any vision system. the methodology used in the plant is based on a hybrid combination of algorithmic determination of the features of a given object with artificial neural networks performing the classification process. An essential aspect of the work is using the advanced camera, which provides three-dimensional image analysis. the obtained verification results confirm the system’s usefulness not only for research purposes but even for implementing industrial automation tasks.
this paper proposes an infinite-time horizon suboptimal control strategy based on state-dependent Riccati equation (SDRE) to control of unmanned ground vehicle (UGV). Cruise control of unmanned robotic platform is mod...
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ISBN:
(数字)9798350362343
ISBN:
(纸本)9798350362350
this paper proposes an infinite-time horizon suboptimal control strategy based on state-dependent Riccati equation (SDRE) to control of unmanned ground vehicle (UGV). Cruise control of unmanned robotic platform is modelled and simulated. For vehicle modelling purpose a full 6 DOF model is considered and described by nonlinear state-space approach. Also a stable state-dependent parametrization (SDP) necessary for solution of the SDRE control problem is proposed and presented. Solution of the SDRE control problem with adequate defined weighting matrices in performance index shows possibility of fast and optimal vehicle control in infinite-time horizon. the method in this form can be used for mission planning of each ground vehicle tracking and dynamics control.
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