Intelligent Control of Electromechanical Complex System
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".
Deadline for manuscript submissions: closed (20 December 2024) | Viewed by 3340
Special Issue Editors
Interests: precision machinery; precision motion control; learning control; system identification
Interests: adaptive parameter estimation; system identification; intelligent control; adaptive control and application
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Traditional control methods often struggle with the nonlinearity, disturbances, and unmodeled dynamics present in complex electromechanical systems, leading to laborious and complex control strategies. With the advent of advanced computational techniques, machine learning algorithms, and abundant measurement data, control strategies for complex electromechanical systems, used in robotics, aerospace, transportation, and wafer scanners, are undergoing a transformative shift from traditional model-based methods to learning-driven control, with the aim of enhancing performance, reliability, and adaptability.
This Special Issue is dedicated to exploring state-of-the-art advancements and innovative approaches in this critical field, both theoretical and application-oriented. It aims to provide a comprehensive platform for researchers, engineers, and practitioners to present their latest findings, share insights, and foster discussions on the intelligent control of complex electromechanical systems. We encourage the submission of theoretical and experimental studies that would promote further research activities in this area. The key topics covered in this issue include, but are not limited to, the following:
- Theoretical foundations for intelligent control;
- Intelligent modeling and identification in electromechanical systems;
- Intelligentization in feedforward and feedback control;
- Intelligent optimization in precision/ultra-precision motion systems;
- Iterative/deep/adaptive learning control for complex systems;
- Intelligent trajectory planning for complex motion systems;
- Sensor fusion and data analytics in electromechanical systems;
- Human–machine interactions in electromechanical systems;
- Application of machine learning and artificial intelligence in electromechanical systems.
Prof. Dr. Yang Liu
Prof. Dr. Jing Na
Dr. Siyuan Zhan
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. Applied Sciences 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
- learning control
- intelligent optimization
- complex electromechanical system
- modeling and identification
- motion control
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
