Advanced Control Techniques for Power Converter and Drives

Dear Colleagues,

In recent years, the field of power electronics and electric drives has witnessed significant advancements propelled by the integration of cutting-edge control methodologies that encompass predictive control, adaptive control, artificial-intelligence-based strategies, and more. These techniques possess the ability to harness the complexities of power converters and drives, transforming them into highly efficient and agile components of modern engineering. Power converters and electric drives play a pivotal role in modern industrial and consumer landscapes, encompassing a broad spectrum of applications such as motor drives, renewable energy systems, electric vehicles, and industrial automation. The intrinsic challenges of enhancing efficiency, maintaining stability, and accommodating diverse operational conditions within these systems have driven researchers and practitioners to explore advanced control techniques. At this juncture, MPC emerges as a compelling solution, offering the capability to predict system behavior over a finite time horizon and optimize control inputs to achieve desired performance objectives.

This Special Issue aims to showcase the latest advancements and research findings in the  domain of advanced control techniques for enhancing the performance, efficiency, and robustness of power converters and electric drives in various applications.

This Special Issue will cover a wide range of topics, including but not limited to:

1. Control Algorithms: The Special Issue will delve into various advanced control algorithms, such as predictive control, adaptive control, fuzzy logic control, and neural-network-based control. These techniques are designed to address complex control challenges and improve system behavior.
2. Dynamic Modeling and Identification: Researchers can present approaches for accurate dynamic modeling and system identification, which are crucial for the successful implementation of advanced control techniques. These models facilitate precise control calculations and optimization.
3. Optimization Objectives: The Special Issue will highlight optimization objectives such as energy efficiency, improved transient response, reduced harmonic distortion, and enhanced stability. These objectives drive the development of advanced control strategies tailored to specific applications.
4. Robustness and Fault Tolerance: Advanced control techniques often incorporate robustness and fault tolerance mechanisms to ensure system stability and reliability in the presence of uncertainties and faults.
5. Real-Time Implementation: Practical considerations for real-time implementation of advanced control techniques will be addressed, including hardware limitations, computational efficiency, and control performance in real-world scenarios.
6. Integration of Renewable Energy: With the increasing integration of renewable energy sources, the Special Issue will explore how advanced control techniques can optimize power converters and drives to accommodate the dynamic nature of renewable energy inputs.
7. Applications: The Special Issue will cover a wide range of applications, including motor drives, renewable energy systems, electric vehicles, industrial automation, and more, demonstrating how advanced control techniques can be tailored to specific application requirements.
8. Hybrid Control Approaches: The Special Issue may also explore hybrid control approaches that combine multiple advanced control techniques to leverage their complementary strengths.

Dr. Daniele Scirè
Dr. Gianpaolo Vitale
Guest Editors

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• advanced control techniques
• power converters
• electric drives
• dynamic modeling
• system identification
• optimization
• fault tolerance
• real-time implementation
• renewable energy integration
• industrial automation