Control and Identification of Industrial Processes
A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".
Deadline for manuscript submissions: 15 July 2026 | Viewed by 515
Special Issue Editors
Interests: real-time applications for advanced control strategies; design of mechatronics systems for industrial processes; multivariable process control; system identifications and nonlinear modeling
Special Issue Information
Dear Colleagues,
Industrial systems are becoming increasingly complex, interconnected, and data-rich, driving the need for advanced control and precise process identification strategies.
This Special Issue focuses on recent progress, emerging trends, and innovative methodologies that enhance the stability, reliability, efficiency, and intelligence of modern industrial processes. It aims to present high-quality contributions that bridge theory and practice, offering both fundamental insights and real-world applicability.
Topics of interest include (but are not limited to) robust, adaptive, and intelligent control; data-driven and learning-based modeling; system identification techniques; optimization-based control; fault detection and diagnosis; nonlinear and distributed control architectures; and hybrid approaches that combine model-based and machine learning paradigms. Contributions addressing industrial applications such as manufacturing automation, process engineering, robotics, power systems, chemical plants, smart factories, and cyber-physical systems are particularly encouraged.
This Special Issue seeks original research articles, case studies, review papers, and application-oriented studies that demonstrate measurable improvements in accuracy, robustness, energy efficiency, safety, or operational performance.
By bringing together advances in modeling, identification, and control design, this Special Issue aims to foster deeper understanding and cross-disciplinary innovation, ultimately supporting the development of next-generation industrial systems that are more adaptive, autonomous, and resilient.
Dr. Ma'Moun Abu-Ayyad
Dr. Nur Syazreen Ahmad
Guest Editors
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 250 words) can be sent to the Editorial Office for assessment.
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. Processes 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 2400 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
- control systems
- intelligent control
- modeling
- machine-learning
- system identification
- optimization
- robotics
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