Convolutional-Neural-Network-Enhanced Intelligent Control Strategies for Smart Actuators and Robotics in Mechatronic Systems
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Robotics, Mechatronics and Intelligent Machines".
Deadline for manuscript submissions: 31 July 2026
Special Issue Editor
Interests: artificial intelligence; robotics; robotic swarm; mechatronics
Special Issue Information
Dear Colleagues,
We are pleased to introduce a forthcoming Special Issue entitled “Convolutional-Neural-Network-Enhanced Intelligent Control Strategies for Smart Actuators and Robotics in Mechatronic Systems.” This Special Issue aims to bring together recent advances at the intersection of deep learning, intelligent control, and mechatronic/robotic actuation, with a particular emphasis on the use of Convolutional Neural Networks (CNNs) to enhance perception, decision-making, and control performance.
Modern mechatronic systems and smart actuators are increasingly required to operate in uncertain, dynamic, and human-centered environments. Combining robust and adaptive control strategies (such as sliding-mode control, model predictive control, and intelligent/adaptive schemes) with CNN-based sensing and feature extraction opens up new opportunities to improve accuracy, robustness, safety, and autonomy in robotics and automation.
This Special Issue welcomes original research articles, case studies, and high-quality review papers on (but not limited to) the following topics:
- CNN-based perception and feedback for smart actuators and robotic systems;
- Intelligent control strategies enhanced by deep learning and data-driven models;
- Robust and adaptive control (e.g., sliding-mode, MPC, nonlinear control) integrated with CNNs;
- Human–robot interaction and collaborative robotics using vision-based control;
- Applications in industrial robotics, service robots, bio-inspired robots, and smart mechatronic devices.
We warmly invite you and your colleagues to consider submitting your latest research to this Special Issue. Your contribution will help advance the state of the art in AI-enhanced intelligent control and robotics.
Should you need further information, please feel free to contact us.
Prof. Dr. Nguyen Truong Thinh
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 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. Machines 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 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
- convolutional neural networks
- intelligent control strategies
- smart actuators
- robotics and mechatronics
- deep learning for control
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