Analysis and Mathematical Modeling of Control Engineering and Path Planning, 2nd Edition
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Engineering Mathematics".
Deadline for manuscript submissions: 1 June 2025 | Viewed by 159
Special Issue Editor
Interests: cyberphysical systems; Industrial Internet of Things; Industry 4.0; resilience; cybersecurity of control systems; WSAN; numerical computing: numerical algorithms library of numerical methods; optimization algorithms; modeling and simulation of control systems for chemical processes; building knowledge bases, fuzzy rule bases, and models based on intelligent agents; decision support systems, machine learning, and fuzzy control systems; prediction and forecasting models for environmental pollution control
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Special Issue Information
Dear Colleagues,
Mathematical modeling is a powerful tool in the context of the transition from Industry 4.0 to Industry 5.0. Migrating from industrial automation to industrial autonomy requires the development of digital twins, a cyber representation of the physical system that must be controlled. Cyber representation is based on mathematical models that also comprise the real-time behavior of the physical process along with its control structure. Industrial autonomy is also based on autonomous robots that must react to the changing environment and tasks according to path planning.
I am pleased to invite you to publish qualitative papers that present new and improved versions of existing mathematical models that have been designed at various observation and representation scales within an industrial control system and are applicable in control engineering and path planning, along with their qualitative and quantitative analysis.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not be limited to) the following: recent advances in mathematical modelling and inverse problems for industrial control systems, and the mathematical modeling of path planning for industrial robots. Articles on real-time simulation, model order reduction, models based on artificial intelligence, and data-driven models are particularly welcome.
Please note that all of the submitted papers must be within the general scope of the Mathematics journal.
I look forward to receiving your contributions.
Dr. Sanda Florentina Mihalache
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- dynamical systems
- numerical methods
- mathematical modeling
- artificial intelligence methods
- mathematical programming
- identification and modeling of control systems
- path planning algorithms
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