Power Converters and AC Electrical Drives with Linear Neural Networks

Maurizio Cirrincione, Marcello Pucci, Gianpaolo Vitale

• Publisher: CRC Press
• Year: 2017
• Print ISBN: 9781138077461
• eBook ISBN: 9781351833943
• Edition: 1
• Topic: Technology & Engineering
• Subtopic: Electrical Engineering & Telecommunications
• Index: Technology & Engineering

The first book of its kind, Power Converters and AC Electrical Drives with Linear Neural Networks systematically explores the application of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical theory based on space-vectors in identification, discusses control of electrical drives and power converters, and examines improvements that can be attained when using linear neural networks.

The book integrates power electronics and electrical drives with artificial neural networks (ANN). Organized into four parts, it first deals with voltage source inverters and their control. It then covers AC electrical drive control, focusing on induction and permanent magnet synchronous motor drives. The third part examines theoretical aspects of linear neural networks, particularly the neural EXIN family. The fourth part highlights original applications in electrical drives and power quality, ranging from neural-based parameter estimation and sensorless control to distributed generation systems from renewable sources and active power filters. Simulation and experimental results are provided to validate the theories.

Written by experts in the field, this state-of-the-art book requires basic knowledge of electrical machines and power electronics, as well as some familiarity with control systems, signal processing, linear algebra, and numerical analysis. Offering multiple paths through the material, the text is suitable for undergraduate and postgraduate students, theoreticians, practicing engineers, and researchers involved in applications of ANNs.

1

Review of Basic Concepts: Space-Vector Analysis

1.1 Introduction

The development of any control system requires the knowledge of the mathematical model describing it. As for electric machines, before the 1950s, only sinusoidal steady-state models were used [1–3]. In these models, the rotating speed is assumed constant, while the voltage or the current supply is sinusoidally time varying. Afterward, dynamic models have been developed, particularly for AC machines [4–6]. These models permit the analysis of the motor behavior during both steady-state and transients with any time-varying waveform of the supply voltage or current. Thus dynamic models have been playing a key role in properly designing control systems of electric drives so that the stability can be achieved with desired time and frequency performance. At the same time, even the electronic power converters have been initially studied only with reference to their input-output steady-state relationship [7]. Afterwards, their dynamic models have been developed which permitted the analysis and design of suitable high-performance control systems as well as novel pulsewidth modulation (PWM) techniques [8–14]. Such control techniques have been adopted in the area of the active rectifier [11–13], the active power filters (APF) [14–16], and the distributed generation systems from renewable sources [17].

A big step ahead in the dynamic modeling of the systems mentioned earlier has been done made thanks to the space-vector theory. This theory has been initially developed with reference to electric machine dynamic study [4–6], but has been then extended to the study of any three-phase system, among which the power converters, for several applications. It is for this reason that, also in this chapter, the space-vector quantity will be initially defined with reference to an AC electric machine, because of its physical meaning, and then extended to other three-phase variable systems. Space-vector theo...

Table of contents

• Cover Page
• Title Page
• Copyright Page
• Dedication Page
• Table of Contents
• Foreword
• Preface
• Acknowledgments
• Authors
• 1 Review of Basic Concepts: Space-Vector Analysis
• Part I Power Converters
• 2 Pulsewidth Modulation of Voltage Source Inverters
• 3 Power Quality
• Part II Electrical Drives
• 4 Dynamic and Steady-State Models of the Induction Machine
• 5 Control Techniques of Induction Machines Drives
• 6 Sensorless Control of Induction Machine Drives
• 7 Permanent Magnet Synchronous Motor Drives
• Part III Neural-Based Orthogonal Regression
• 8 Neural-Based Orthogonal Regression
• Part IV Selected Applications
• 9 Least-Squares and Neural Identification of Electrical Machines
• 10 Neural-Enhanced Single-Phase DG Systems with APF Capability
• 11 Neural Sensorless Control of AC Drives
• Index