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A Novel Design Approach of a Nonlinear Resistor Based on a Memristor Emulator Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Swarm Intelligence PID Controller Tuning for AVR System

Authors : Naglaa K. Bahgaat, M. A. Moustafa Hassan

Published in: Advances in Chaos Theory and Intelligent Control

Publisher: Springer International Publishing

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Abstract

The voltage regulator is designed to automatically maintain a constant voltage level in the power system. It may be used to regulate one or more AC or DC voltages in power systems. Voltage regulator may be designed as a simple “feed-forward” or may include “negative feedback” control loops. Depending on the design, it may use an electromechanical mechanism, or electronic components. The role of an AVR is to keep constant the output voltage of the generator in a specified range. The PID controller can used to provide the control requirements.The chapter discusses the methods to get the best possible tuning controller parameters for an automatic voltage regulator (AVR) system of a synchronous generator. It was necessary to use PID controller to increase the stability margin and to improve performance of the system. Some modern techniques were defined. These techniques as Particle Swarm Optimization (PSO), also it illustrates the use of a Adaptive Weight Particle Swarm Optimization (AWPSO), Adaptive Acceleration Coefficients based PSO, (AACPSO), Adaptive Acceleration Coefficients based PSO (AACPSO). Furthermore, it introduces a new modification for AACPSO technique, Modified Adaptive Acceleration Coefficients based PSO (MAAPSO) is the new technique which will be discussed inside the chapter, A comparison between the results of all methods used will be given in this chapter. Simulation for comparison between the proposed methods will be displayed. The obtained results are promising.

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Metadata
Title
Swarm Intelligence PID Controller Tuning for AVR System
Authors
Naglaa K. Bahgaat
M. A. Moustafa Hassan
Copyright Year
2016
Book
Advances in Chaos Theory and Intelligent Control

Print ISBN: 978-3-319-30338-3

Electronic ISBN: 978-3-319-30340-6

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-30340-6_33

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