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Design of neural network predictive controller based on imperialist competitive algorithm for automatic voltage regulator

  • M. ElsisiEmail author
Original Article
  • 28 Downloads

Abstract

This paper proposes the neural network (NN) predictive controller that combines the advantages of NN and predictive control for the automatic voltage regulator (AVR). The NN predictive controller is suggested as a new intelligence controller rather than the conventional controllers for the AVR. This is the first application of the NN predictive controller for AVR. There are five parameters of the NN predictive controller which need a proper tuning to get a good performance by using the NN predictive controller. In recent papers, the parameters of NN predictive controller are typically set by trial and error or by the designer’s expertise. The imperialist competitive algorithm (ICA) is introduced in this paper as a new artificial intelligence technique instead of the trial-and-error or the designer’s expertise methods to get the optimal parameters of NN predictive controller in order to overcome the deviations of the voltage. The performance of the designed NN predictive controller based on the ICA is compared with the designed NN predictive controller based on the genetic algorithm and the conventional proportional–integral–derivative controller based on Ziegler–Nichols technique. The comparison emphasizes the superiority of the suggested NN predictive controller based on the ICA.

Keywords

Imperialist competitive algorithm (ICA) Automatic voltage regulator (AVR) Neural network (NN) predictive controller 

List of symbols

N1

The minimal prediction horizon of the output

N2

The maximal prediction horizon of the output

Nu

The control horizon

u

Tentative control signal

yr

The target response

ym

The network model response

ρ

The weight of the control signal

β

A number > 1

d

The distance between colony and imperialist

γ

A limit angle

Vref

The reference voltage

Vt

The output terminal voltage

e

The error signal

u

The control signal

KA

The amplifier gain

TA

The amplifier time constant

KE

The exciter gain

TE

The exciter time constant

KG

The generator gain

TG

The generator time constant

KS

The sensor gain

TS

The sensor time constant

Notes

Compliance with ethical standards

Conflict of interest

Author states that there are no conflicts of interest.

Ethical approval

This article does not contain any studies with human participants performed by any of the authors.

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Electrical Power and Machines Department, Faculty of Engineering (Shoubra)Benha UniversityCairoEgypt

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