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

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...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2007-02, Vol.54 (1), p.14-33
Main Author: Bose, B.K.
Format: Article
Language:English
Subjects:
Artificial intelligence
Artificial neural networks
Backpropagation network
Control systems
Control theory
Delay estimation
Electronics
induction motor drive
Intelligent control
intelligent control and estimation
Mathematical analysis
Motor drives
Motors
neural network
Neural networks
Neurofeedback
perceptron
Power electronics
Pulse duration modulation
Pulse width modulation inverters
recurrent network
Space technology
space vector PWM
Studies
Vectors (mathematics)
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Description
Summary: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
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2006.888683