Special Issue "Control of Nonlinear Systems and Industrial Processes"
Deadline for manuscript submissions: 10 June 2021.
Interests: control systems for industrial processes; digital control systems
Interests: control theory; control engineering
Interests: fault detection; control systems engineering
Interests: control systems engineering; real time control systems; nonlinear control
Most technologies and processes, through their interactions, laws, and dynamics, present a nonlinear behavior. The nonlinearities have a stronger impact with the increase in the system’s complexity and dynamics. In these circumstances, the role of nonlinear control in industrial processes becomes more and more crucial.
The abstract representation through nonlinear system modeling offers an important field of research based on the support provided by mathematics, modern systems theory, as well as the development of digital systems and their joint computational assets. These essential tools operate with data, hardware, and software resources, in order to find practical solutions in different applications and to contribute to the development of innovative management strategies for industrial systems and processes.
This Special Issue on “Control of Nonlinear Systems and Industrial Processes”, part of the Electronics MDPI Journal, offers a framework for the presentation of scientific research that brings interesting and relevant contributions in the field of nonlinear control systems and control of industrial processes.
At the same time, the journal provides opportunities for the authors, researchers, and specialists, to offer and to promote their recent developments and relevant results in nonlinear control theory and process control design, applied to different domains with technical and industrial interest, for example, energy, transport, automotive, chemistry and petrochemistry, aerospace, biotechnology, telecommunications, etc.
The journal invites original submissions addressing subjects regarding system stability, control robustness, high computational performance and design for nonlinear systems, issues that arise in process exploitation, aiming at control and management of real-time practical applications, by means of advanced control methods, artificial intelligence or machine learning resources.
Prof. Dr. Dumitru Popescu
Prof. Dr. Haoping Wang
Prof. Dr. Severus C. Olteanu
Prof. Dr. Ciprian Lupu
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 papers will be 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. Electronics is an international peer-reviewed open access monthly 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 1500 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.
- Modeling and simulation of nonlinear systems
- Linearized techniques and nonlinear control systems
- Extremal control for systems with nonlinearities
- Optimal control for systems with parametric uncertainties
- Robust control for nonlinear systems
- Design for multicontroller–multimodel (MCMM) configurations
- Supervisory nonlinear control
- Identification techniques for industrial processes
- Model-based control design for linear and nonlinear processes
- Process control design for real time applications
- Adaptive and robust control
- Intelligent control
- Fuzzy and neural control
- Control and robotics
- HiL configurations for simulation and control
- Key distributed and hierarchical architectures for process control
- Process control applications