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Unformatted text preview: 14 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 54, NO. 1, FEBRUARY 2007 Neural Network Applications in Power Electronics and Motor Drives—An Introduction and Perspective Bimal K. Bose , Life Fellow, IEEE Invited Paper 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 com- prehensive introduction and perspective of neural network appli- cations in the intelligent control and estimation for power elec- tronics 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 applica- tion 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. Ad- ditional 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. Index Terms— Backpropagation network, induction motor drive, intelligent control and estimation, neural network, percep- tron, recurrent network, space vector PWM. I. INTRODUCTION T HE ARTIFICIAL INTELLIGENCE (AI) techniques, such as expert system (ES), fuzzy logic (FL), artificial neural network (ANN or NNW), and genetic algorithm (GA) have recently been applied widely in power electronics and motor drives. The goal of AI is to plant human or natural intelligence in a computer so that a computer can think intelligently like a human being. A system with embedded computational in- telligence is often defined as an “intelligent system” that has “learning,” “self-organizing,” or “self-adapting” capability. Computational intelligence has been debated for a long time, and will possibly be debated for ever. However, there is no denying the fact that computers can have adequate intelligence to help solving our problems that are difficult to solve by traditional methods. Therefore, it is true that AI techniques Manuscript received May 15, 2006; revised September 9, 2006. Abstract pub- lished on the Internet November 30, 2006....
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This note was uploaded on 01/19/2010 for the course YSA ANN taught by Professor Asd during the Spring '09 term at Koç University.

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