In the book Handbook of Power Electronics in Smart Grids and Intelligent Energy
Academic Press, Cambridge, United States of America
Summary
This chapter explores the integration of artificial neural networks (ANNs) into power electronics and electric drives, focusing on their ability to address challenges such as system nonlinearity, real-time adaptation, and fault detection. The chapter provides an overview of ANN fundamentals, including their architecture and training methods, followed by applications in areas like DC–DC converter control, power oscillation damping, and fault diagnosis in induction motors. Experimental validations demonstrate that ANN-based controllers outperform traditional methods in precision, stability, and dynamic response. Despite challenges like computational demands and data requirements, ANNs offer transformative potential for improving efficiency, reliability, and adaptability in modern power systems.
Editors: M.H. Rashid
ISBN: 978-0-323-95045-9
DOI: 
https://doi.org/10.1016/B978-0-323-95045-9.00016-0
DOI of the book:
https://doi.org/10.1016/C2021-0-02619-5
Published: 2026
Citation:
C.D. Zuluaga-Ríos, "Artificial neural networks applications in power electronics and electric drives", in Handbook of Power Electronics in Smart Grids and Intelligent Energy, M.H. Rashid Ed. Cambridge, United States of America: Ed. Academic Press, 2026, pp. 545-561, doi: 10.1016/B978-0-323-95045-9.00016-0
IIT-26-138L
