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Related Experiment Video

Updated: May 9, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Fractional adaptive control for an automatic voltage regulator.

Norelys Aguila-Camacho¹, Manuel A Duarte-Mermoud

¹Department of Electrical Engineering, University of Chile, Av. Tupper 2007, Santiago de Chile, Chile; Advanced Mining Technology Center, Av. Tupper 2007, Santiago de Chile, Chile.

ISA Transactions

|July 11, 2013

Summary

This study applies a direct Fractional Order Model Reference Adaptive Controller (FOMRAC) to Automatic Voltage Regulators (AVRs). FOMRAC enhances system performance and robustness against uncertainties compared to traditional controllers.

Keywords:

Automatic voltage regulator Fractional order adaptive control Genetic algorithms optimization Model reference adaptive control

Related Experiment Videos

Last Updated: May 9, 2026

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator

Published on: October 28, 2022

Area of Science:

Control Systems Engineering
Electrical Engineering
Adaptive Control Theory

Background:

Automatic Voltage Regulators (AVRs) are critical for grid stability.
Traditional controllers face challenges with system uncertainties and performance limitations.

Purpose of the Study:

To apply a direct Fractional Order Model Reference Adaptive Controller (FOMRAC) to an AVR system.
To evaluate FOMRAC's effectiveness against various control strategies.

Main Methods:

Designed four direct FOMRAC realizations with varying fractional orders.
Optimized fractional orders and adaptive gains using Genetic Algorithm.
Compared FOMRAC performance against FOPID, PID, and IOMRAC controllers.

Main Results:

FOMRAC demonstrated improved controlled system behavior.
Enhanced robustness against model uncertainties was observed.
Performance indices highlighted FOMRAC's advantages and disadvantages.

Conclusions:

Direct FOMRAC offers superior performance and robustness for AVRs.
Fractional order adaptive control presents a promising alternative for power system regulation.