作者:
Edu, Emil-RonaldRadac, Mircea-Bogdan
Department of Mechanical Engineering Timisoara Romania PUT
Dept. of Automation and Applied Informatics Timisoara Romania
In the present paper, the operation of high-power wind turbines of the order of mega-watts (MW), is analysed at significantly variable wind speeds over time. Experimental data from a wind turbine operating in the Dobr...
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This paper merges the advantages of data-driven control and sliding mode control in terms of applying and modifying two combinations of model-free adaptive control and sliding mode control suggested by Ebrahimi et al....
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The two-wheeled inverted pendulum (WIP) is an unstable nonlinear system used in industrial and academic applications. Two control methods for WIP-based self-balancing robot are developed, implemented in Matlab-Simulin...
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This paper introduces a robust sensorless control system for permanent magnet synchronous motor (PMSM) drives using the active flux observer with serial combined PMSM voltage and current models. To assure system robus...
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The paper explores the current challenges in software modeling of real-time applications for complex distributed systems taking benefits of the current abstracted mechanisms and graphical elements supported by UML and...
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In the present paper, the operation of high-power wind turbines of the order of mega-watts (MW), is analysed at significantly variable wind speeds over time. Experimental data from a wind turbine operating in the Dobr...
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ISBN:
(数字)9798350395914
ISBN:
(纸本)9798350395921
In the present paper, the operation of high-power wind turbines of the order of mega-watts (MW), is analysed at significantly variable wind speeds over time. Experimental data from a wind turbine operating in the Dobrogea region are processed, at a higher sampling frequency of measurements. The current operating condition is investigated from an efficiency viewpoint and compared with an optimized controlled setting, in which the electric generator power is controlled dependent on the wind speed value. We find that wind speed sampling frequency is an important factor impacting control quality, while the improved control is mandatory for maximal operation efficiency.
This paper merges the advantages of data-driven control and sliding mode control in terms of applying and modifying two combinations of model-free adaptive control and sliding mode control suggested by Ebrahimi et al....
This paper merges the advantages of data-driven control and sliding mode control in terms of applying and modifying two combinations of model-free adaptive control and sliding mode control suggested by Ebrahimi et al. in 2018 to the position control of tower crane systems. The modifications concern the classical definition of the control error or the tracking error and appropriate proofs are adapted and summarized. The two controllers are validated experimentally and compared in the control of the three positions specific to tower crane system laboratory equipment.
A comparative study of two mixes of data-driven algorithms is proposed in this paper. The discrete-time second-order model-free control known as an intelligent Proportional (iP) controller is tuned considering Virtual...
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The paper describes the design and implementation of an open source machine vision platform for visual robot guidance and automated product inspection in manufacturing, based on OpenCV library. Using this platform, th...
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The paper describes the design and implementation of an open source machine vision platform for visual robot guidance and automated product inspection in manufacturing, based on OpenCV library. Using this platform, the rigid, industry-specific organization of material flows can be relaxed, shop floor resources becoming reality-aware. The main functionalities are: acquisition of video streams from multiple sources, image analysis at scene level, part recognition, locating and interaction with industrial equipment using standard, open communication protocols. The paper describes design aspects: system architecture, data acquisition and standardization of the image representation used by the analysis algorithms and object recognition module and input/output interaction protocols for a set of predefined cases. Results are reported for an implementation of the platform using a commercial image acquisition device and an industrial robot.
A big volume of new data is generated in every moment of the day by different devices and domains as social network, mobile and desktop devices, financial transaction, online websites, different search engines and a l...
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A big volume of new data is generated in every moment of the day by different devices and domains as social network, mobile and desktop devices, financial transaction, online websites, different search engines and a lot of smart home devices. The generated data is diversified and can be structured or unstructured. Clustering is the process of categorizing a dataset in groups of records that are similar and are called clusters, the grouping process being performed using a specific criterion. The K-means clustering algorithm is still popular after many years. Different versions of the K-means algorithm emerged along the time and were focused on improving the K-means algorithm by performing some preprocessing steps or by reducing the number of iterations having as a final objective the improvement of the processing time. This paper presents a way of improving the resulted clusters generated by the K-means algorithm by post processing the resulted clusters with a supervised learning algorithm. The proposed approach is focused on improving the quality of the resulting clusters and not on reducing the processing time.
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