WSEAS Transactions on Signal Processing
Print ISSN: 1790-5052, E-ISSN: 2224-3488
Volume 17, 2021
One-Step Predictive H2 FIR Tracking under Persistent Disturbances and Data Errors
Authors: Oscar Ibarra-Manzano, Jose Andrade-lucio, Yuriy S. Shmaliy, Yuan Xu
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
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Keywords: Industrial errors, object tracking, H2 FIR predictor, Kalman predictor, unbiased FIR predictor
Pages: 87-92
DOI: 10.37394/232014.2021.17.12
WSEAS Transactions on Signal Processing, ISSN / E-ISSN: 1790-5052 / 2224-3488, Volume 17, 2021, Art. #12