Artificial Intelligence in Advanced Motor Drives and Robotic Motion Control
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".
Deadline for manuscript submissions: 15 October 2026 | Viewed by 150
Special Issue Editors
Interests: motor drive control; servo system control; grid-forming converter control; control theory; permanent magnet synchronous motor; variable-pole machine; microgrid optimization and control; virtual power plant optimization
Special Issues, Collections and Topics in MDPI journals
Interests: intelligent control; neural networks; robotic systems; adaptive control
Special Issues, Collections and Topics in MDPI journals
Interests: pattern recognition; artificial intelligence and deep learning networks; intelligent systems
Special Issues, Collections and Topics in MDPI journals
Interests: multi-agent systems; path planning and decision; state estimation; intelligent systems
Special Issues, Collections and Topics in MDPI journals
Interests: renewable energy systems; nonlinear control systems; intelligent systems; robot technology
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid evolution of Industry 5.0 and the increasing demand for autonomous systems have placed unprecedented requirements on the precision, efficiency, and adaptability of robotic systems. At the heart of these systems lies the seamless integration of motor drive units and high-level motion control strategies. While traditional control methods like PID and FOC have served the industry for decades, they often struggle to handle non-linearities, parameter variations, and complex dynamic environments inherent in modern robotics.
Aims and Scope: This Special Issue focuses on the transformative role of Artificial Intelligence (AI) and advanced computational intelligence in bridging the gap between electrical drive hardware and robotic applications. The scope encompasses a wide range of topics, including but not limited to the following:
- Deep Reinforcement Learning (DRL) for high-performance motor control;
- Neural network-based observers for sensorless control and parameter estimation;
- AI-driven fault diagnosis and predictive maintenance for robotic drive trains;
- Intelligent motion planning and multi-axis coordination using machine learning;
- Edge AI implementation in motor controllers and embedded robotic systems.
Relationship to Existing Literature: While existing literature often treats motor drives (power electronics) and robotic control (automation) as isolated domains, this topical collection aims to supplement the field by emphasizing synergistic integration. It moves beyond generic AI applications by focusing on "Control-Oriented AI"—algorithms that respect the real-time constraints and physical laws of electromechanical systems. By collecting cutting-edge research on intelligent actuators and smart motion control, this Issue will provide a comprehensive reference for researchers looking to implement AI in practical, high-bandwidth robotic hardware, thus filling the gap between theoretical machine learning and industrial implementation.
We invite original research and review articles that explore new frontiers in intelligent motion systems, aiming to define the next generation of smart, responsive, and reliable robotic drives.
Dr. Xinpo Lin
Dr. Zhuang Liu
Prof. Dr. Yue Zhao
Prof. Dr. Yabin Gao
Prof. Dr. Jianxing Liu
Guest Editors
Manuscript Submission Information
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Keywords
- artificial intelligence
- motor drives
- robotic motion control
- deep reinforcement learning
- intelligent actuators
- fault diagnosis
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