Learning Based Control for Autonomous Systems
A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Automation and Control Systems".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 136
Special Issue Editor
Interests: networked control systems; learning based control
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, machine learning has achieved remarkable progress and has increasingly been integrated into control systems for autonomous platforms. Techniques such as neural networks, reinforcement learning, and data-driven system identification have demonstrated strong capabilities in modeling complex dynamics, approximating control policies, and improving adaptability in uncertain environments. These advances have enabled new possibilities for autonomous systems operating in highly nonlinear, high-dimensional, and partially unknown settings.
However, many existing learning-based control approaches remain largely heuristic and empirical in nature. Despite impressive performance in simulations and experiments, they often lack rigorous theoretical guarantees on stability, robustness, and safety—properties that are essential for deploying autonomous systems in safety-critical applications such as aerospace, robotics, and intelligent transportation.
This Special Issue aims to bring together recent advances in learning-based control with formal guarantees for autonomous systems. We particularly welcome contributions that integrate machine learning with control theory to provide provable stability, safety, robustness, and performance assurances. Topics of interest include, but are not limited to, learning-enabled controller synthesis, safe reinforcement learning, stability-certified neural network control, data-driven robust control, and theoretical analysis of learning-based closed-loop systems.
The goal is to foster research that bridges the gap between data-driven intelligence and rigorous control-theoretic foundations.
Prof. Dr. Liang Xu
Guest Editor
Manuscript Submission Information
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Keywords
- learning-based control
- autonomous systems
- stability analysis
- safety-critical control
- safe reinforcement learning
- neural network control
- data-driven control
- robust control
- formal guarantees
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