Review of modern nonlinear control methods
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F25%3A63599881" target="_blank" >RIV/70883521:28140/25:63599881 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-031-94223-5_24" target="_blank" >http://dx.doi.org/10.1007/978-3-031-94223-5_24</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-031-94223-5_24" target="_blank" >10.1007/978-3-031-94223-5_24</a>
Alternative languages
Result language
angličtina
Original language name
Review of modern nonlinear control methods
Original language description
Nonlinear control methods are essential for effective control of complicated dynamic systems, particularly when conventional linear techniques are ineffective. The paper presents an extensive review of contemporary nonlinear control techniques, paying particular attention to their categorization, theoretical backgrounds, and real-world applications. The study starts with the introduction of nonlinear system properties and mathematical modeling, followed by a bibliometric analysis that illustrates the increasing popularity of the research topic. The article classifies nonlinear control methodologies into two broad categories: system linearization-based and nonlinear control law-based direct approaches. Adaptive control, Nonlinear Model Predictive Control, and Artificial Intelligence-based control methodologies are investigated in detail and systematically compared based on recent experimental findings. Particular emphasis is placed on novel developments, e.g., data-driven control methods and optimization-based techniques, which have shown encouraging results in practical applications. The results emphasize the growing role of machine learning and model-free methods in nonlinear control. The review is a valuable resource for researchers and practitioners interested in getting acquainted with state-of-the-art nonlinear control techniques and their changing background.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Mechanical Engineering
ISBN
978-3-031-94222-8
ISSN
2195-4356
e-ISSN
2195-4364
Number of pages
10
Pages from-to
265-274
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Berlín
Event location
Praha
Event date
Jun 18, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—