Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective

TLDR

Artificial intelligence, especially neural networks, is reshaping power electronics and motor drives, a complex, multidisciplinary field undergoing rapid evolution. This paper offers a comprehensive introduction and perspective on neural‑network applications for intelligent control and estimation in power electronics and motor drives. The authors review application examples—including nonlinear function generation, delay‑less filtering, waveform processing, vector‑drive feedback signal processing, space‑vector PWM for two‑ and multilevel inverters, adaptive flux‑vector estimation, and combined vector‑controlled AC drive techniques—and reference additional literature. Current trends suggest that neural networks will become widely adopted in power electronics and motor drives.

Abstract

Artificial intelligence (AI) techniques, particularly the neural networks, are recently having significant impact on power electronics and motor drives. Neural networks have created a new and advancing frontier in power electronics, which is already a complex and multidisciplinary technology that is going through dynamic evolution in the recent years. This paper gives a comprehensive introduction and perspective of neural network applications in the intelligent control and estimation for power electronics and motor drives area. The principal topologies of neural networks that are currently most relevant for applications in power electronics have been reviewed including the detailed description of their properties. Both feedforward and feedback or recurrent architectures have been covered in the description. The application examples that are discussed in this paper include nonlinear function generation, delayless filtering and waveform processing, feedback signal processing of vector drive, space vector PWM of two-level and multilevel inverters, adaptive flux vector estimation, and some of their combination for vector-controlled ac drive. Additional selected applications in the literature are included in the references. From the current trend of the technology, it appears that neural networks will find widespread applications in power electronics and motor drives in future