My Account Log in

1 option

Automation 2024: Advances in Automation, Robotics and Measurement Techniques / edited by Roman Szewczyk, Cezary Zieliński, Małgorzata Kaliczyńska, Vytautas Bučinskas.

Springer eBooks EBA - Intelligent Technologies and Robotics Collection 2024 Available online

View online
Format:
Book
Author/Creator:
Szewczyk, Roman.
Contributor:
Zieliński, Cezary.
Kaliczyńska, Małgorzata.
Bučinskas, Vytautas.
Series:
Lecture Notes in Networks and Systems, 2367-3389 ; 1219
Language:
English
Subjects (All):
Automatic control.
Robotics.
Automation.
Computational intelligence.
Artificial intelligence.
Control, Robotics, Automation.
Computational Intelligence.
Artificial Intelligence.
Local Subjects:
Control, Robotics, Automation.
Computational Intelligence.
Artificial Intelligence.
Physical Description:
1 online resource (374 pages)
Edition:
1st ed. 2024.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Summary:
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.
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
9783031782664
3031782666
OCLC:
1493030803

The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.

My Account

Shelf Request an item Bookmarks Fines and fees Settings

Guides

Using the Library Catalog Using Articles+ Library Account