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Automation 2024 = advances in automation, robotics and measurement techniques /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Automation 2024/ edited by Roman Szewczyk ... [et al.].
Reminder of title:	advances in automation, robotics and measurement techniques /
other author:	Szewczyk, Roman.
corporate name:	International Conference Automation
Published:	Cham :Springer Nature Switzerland : : 2024.,
Description:	xii, 368 p. :ill., digital ;24 cm.
[NT 15003449]:	Research towards an optimal method of modeling and regulating a cement mill using AI algorithms -- New sliding hyperplane for achieving bounded output performance in DSMC -- Applicability of Fractional-Order PID Controllers for Twin Rotor Aerodynamic System Objects -- Employing Generative Artificial Intelligence in Replacement of Traditional Backend Systems -- Failure Modeling of Industrial Electric Motors using Unsupervised Learning Methods -- Automatic functional tests of cash registers -- Hyperspectral lighting design for industrial applications.
Contained By:	Springer Nature eBook
Subject:	Automatic control - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-031-78266-4
ISBN:	9783031782664

Automation 2024 = advances in automation, robotics and measurement techniques /
Automation 2024advances in automation, robotics and measurement techniques /[electronic resource] :edited by Roman Szewczyk ... [et al.]. - Cham :Springer Nature Switzerland :2024. - xii, 368 p. :ill., digital ;24 cm. - Lecture notes in networks and systems,12192367-3389 ;. - Lecture notes in networks and systems ;1219..

Research towards an optimal method of modeling and regulating a cement mill using AI algorithms -- New sliding hyperplane for achieving bounded output performance in DSMC -- Applicability of Fractional-Order PID Controllers for Twin Rotor Aerodynamic System Objects -- Employing Generative Artificial Intelligence in Replacement of Traditional Backend Systems -- Failure Modeling of Industrial Electric Motors using Unsupervised Learning Methods -- Automatic functional tests of cash registers -- Hyperspectral lighting design for industrial applications.

This book presents the result of the most recent discussion among interdisciplinary specialists facing scientific and industrial challenges. The papers presented during the Automation 2024 Conference deal with applying artificial neural networks and other machine learning methods in perception, modelling, and control, utilization of fractional order systems, and novel sensors and measurement techniques. Recent developments in robotics and the quality of exerted control and optimization are also prominent in this volume. Specific aspects of the design of diverse robots and their modelling and control are described in depth. We strongly believe that the solutions and guidelines presented in this book will be useful to both researchers and engineers during the development of automation, robotics, and measurement systems in a rapidly changing global industry.

ISBN: 9783031782664

Standard No.: 10.1007/978-3-031-78266-4doiSubjects--Topical Terms:

658360
Automatic control
--Congresses.

LC Class. No.: TJ212.2 / .I58 2024

Dewey Class. No.: 629.8

Automation 2024 = advances in automation, robotics and measurement techniques /
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490 1 $a Lecture notes in networks and systems, $x 2367-3389 ; $v 1219
505 0 $a Research towards an optimal method of modeling and regulating a cement mill using AI algorithms -- New sliding hyperplane for achieving bounded output performance in DSMC -- Applicability of Fractional-Order PID Controllers for Twin Rotor Aerodynamic System Objects -- Employing Generative Artificial Intelligence in Replacement of Traditional Backend Systems -- Failure Modeling of Industrial Electric Motors using Unsupervised Learning Methods -- Automatic functional tests of cash registers -- Hyperspectral lighting design for industrial applications.
520 $a This book presents the result of the most recent discussion among interdisciplinary specialists facing scientific and industrial challenges. The papers presented during the Automation 2024 Conference deal with applying artificial neural networks and other machine learning methods in perception, modelling, and control, utilization of fractional order systems, and novel sensors and measurement techniques. Recent developments in robotics and the quality of exerted control and optimization are also prominent in this volume. Specific aspects of the design of diverse robots and their modelling and control are described in depth. We strongly believe that the solutions and guidelines presented in this book will be useful to both researchers and engineers during the development of automation, robotics, and measurement systems in a rapidly changing global industry.
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