Advanced Nonlinear and Learning-Based Control Techniques for Complex Dynamical Systems, 2nd Edition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".
Deadline for manuscript submissions: 20 June 2024 | Viewed by 1437
Special Issue Editors
Interests: thermoacustics; synthetic jet actuators; flow-induced-noise control; marine vehicle control; flow control
Special Issues, Collections and Topics in MDPI journals
Interests: real-time learning-based control; machine learning; multi-agent systems; control & systems theory; robotics
Special Issues, Collections and Topics in MDPI journals
Interests: real-time optimization-based control and estimation methods, nonlinear control, and machine learning, with special emphasis on foundational theory and experimental realization on robotic and autonomous systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
There has been a great deal of excitement during the recent past over the emergence of new mathematical techniques for the modeling and analysis of complex dynamical systems. For example, recent years have witnessed an explosion of work on the development of both learning-based and nonlinear control system models in a geometric form that are globally defined without singularities or ambiguities. These models are applied to the motion planning and feedback control of constrained robotic systems. These fascinating topics require the use of diverse parts of mathematics. Nonlinear and learning-based control system theory and various design techniques are used widely in the robotics arena, especially in developing nonlinear robust control algorithms. The design of these systems involves advanced techniques including nonlinear optimization, machine learning, adaptive estimation, and nonlinear observer and control design methodologies. In this context, this Special Issue welcomes the submission of papers from a wide range of researchers in applied mathematics and various engineering disciplines.
Potential topics include, but are not limited to:
- Nonlinear optimization techniques;
- Nonlinear observer design;
- Nonlinear adaptive estimation;
- Nonlinear robust control;
- Reduced-order modeling and control;
- Learning-based/intelligent control;
- Neuro-adaptive control;
- Gaussian-process-based control methods;
- Real-time learning-based control;
- Multi-agent systems control;
- Formation/flocking control;
- Geometric control theory and applications.
Prof. Dr. Mahmut Reyhanoglu
Dr. Mohammad Jafari
Dr. Erkan Kayacan
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 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 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
- optimization
- observer design
- adaptive control
- learning control
- intelligent control
- robust control
- formation control
- geometric control
