Direct Adaptive Inverse Control via Fractional Least Mean Square
Authors
Mr. Rodrigo Noronha, Instituto Federal de Educação Ciência e Tecnologia do Maranhão, Imperatriz, Brazil
Abstract
In this work, a new methodology of Direct Adaptive Inverse Control (DAIC) via Fractional Least Mean Square (FLMS) algorithm is proposed. The convergence speed and the steady-state Mean Square Error (MSE) during the update of the estimation of a weights vector through a adaptive algorithm is a fundamental issue for a good performance of adaptive filters. In this context, it was performed the performance analysis of FLMS algorithm, in terms of convergence speed and steady-state MSE, during the update of the weights vector of the controller, which is based on adaptive Finite Impulse Response (FIR) filter. The proposed control methodology was evaluated on a non-minimum phase plant in the presence of a periodic disturbance signal added to the control signal.
1st Mosharaka International Conference on Control and Systems Engineering (MIC-Control 2021)
Congress
2021 Global Congress on Electrical Engineering (GC-ElecEng 2021), 10-12 December 2021, Valencia, Spain
Pages
--1
Topics
Adaptive Control Systems Robust Control
ISSN
2227-331X
DOI
BibTeX
@inproceedings{1187ElecEng2021,
title={Direct Adaptive Inverse Control via Fractional Least Mean Square},
author={Rodrigo Noronha},
booktitle={2021 Global Congress on Electrical Engineering (GC-ElecEng 2021)},
year={2021},
pages={--1},
doi={}},
organization={Mosharaka for Research and Studies}
}
