One-Step Predictive H2 FIR Tracking under Persistent Disturbances and Data Errors

Author:

IBARRA-MANZANO OSCAR1,ANDRADE-LUCIO JOSE1,SHMALIY YURIY S.1,XU YUAN2

Affiliation:

1. Department of Electronics Engineering, University of Guanajuato Salamanca, 36885, MEXICO

2. School of Electrical Engineering, University of Jinan, Jinan 250022, CHINA

Abstract

Information loss often occurs in industrial processes under unspecified impacts and data errors. Therefore robust predictors are required to assure the performance. We design a one-step H2 optimal finite impulse response (H2-OFIR) predictor under persistent disturbances, measurement errors, and initial errors by minimizing the squared weighted Frobenius norms for each error. The H2-OFIR predictive tracker is tested by simulations assuming Gauss-Markov disturbances and data errors. It is shown that the H2-OFIR predictor has a better robustness than the Kalman and unbiased FIR predictor. An experimental verification is provided based on the moving robot tracking problem

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

Computer Networks and Communications,Computer Vision and Pattern Recognition,Signal Processing,Software

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