Control Systems in Mechatronics and Robotics
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: 20 June 2026 | Viewed by 1278
Special Issue Editors
Interests: nonlinear systems; robotics; underactuated systems; neural networks; complex systems; mechatronics; aerial autonomous systems
Special Issues, Collections and Topics in MDPI journals
Interests: control systems; autonomous systems; computer vision; aerial autonomous systems
Special Issues, Collections and Topics in MDPI journals
Interests: aerial autonomous systems; nonlinear control design; wheeled mobile robot control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Control systems are integral to the development and operation of mechatronic and robotic systems, serving as the backbone that ensures precise and reliable performance across various applications. Mechatronics, a multidisciplinary field that combines mechanical engineering, electronics, computer science, and control engineering, relies heavily on sophisticated control strategies to optimize system functionality. As technology advances, the complexity and demands of mechatronic systems increase, necessitating innovative control solutions that can handle dynamic environments and intricate interactions between components.
In robotics, control systems facilitate the autonomous operation of robots, enabling them to perform tasks ranging from simple assembly to complex interactions in uncertain environments. Effective control algorithms are essential for tasks such as motion planning, path following, and sensor integration, allowing robots to adapt to changes in their surroundings while maintaining accuracy and stability.
The emergence of new technologies, such as artificial intelligence and machine learning, has further transformed the landscape of control systems in mechatronics and robotics. These advancements enable the development of adaptive and intelligent control strategies that can learn from experience and improve over time, paving the way for smarter and more autonomous systems.
Despite significant progress, challenges remain in the design and implementation of control systems, particularly in terms of robustness, real-time performance, and integration with other technologies. This Special Issue aims to explore the latest research and developments in control systems within the context of mechatronics and robotics, addressing both theoretical and practical aspects. By highlighting innovative solutions and emerging trends, we hope to contribute to the ongoing evolution of these fields, fostering collaboration and inspiring future research.
The primary objective of this Special Issue is to gather recent findings on control systems in mechatronics, with a particular focus on both practical and theoretical challenges. We aim to highlight efficient implementations in various applications, as well as innovative designs that demonstrate their benefits through simulations or real-time experiments.
The topics of this Special Issue cover a wide range of important applications, such as:
- Advanced control algorithms (PID, adaptive control, etc.)
- Machine learning and AI in control systems
- Nonlinear control strategies
- Real-time control applications
- Control of autonomous systems
- Networked control systems
- Modeling
- Real-time embedded system;
- Practical challenges in implementation
- Simulation
Prof. Dr. Javier Moreno-Valenzuela
Dr. Luis Rodolfo Garcia Carrillo
Prof. Dr. Alejandro Enrique Dzul López
Guest Editors
Manuscript Submission Information
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Keywords
- advanced control algorithms
- machine learning and AI in control systems
- nonlinear control strategies
- real-time control applications
- control of autonomous systems
- networked control systems
- modeling
- real-time embedded system
- practical challenges in implementation
- simulation
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