Robust adaptive estimators for nonlinear systems

Tools

Abdul Wahab, Hamimi Fadziati Binti and Katebi, Reza (2013) Robust adaptive estimators for nonlinear systems. In: Conference on Control and Fault-Tolerant Systems (SysTol), 2013, 2013-10-09 - 2013-10-11. (https://doi.org/10.1109/SysTol.2013.6693823)

[thumbnail of Robust Adaptive Estimators for Nonlinear Systems_final]
Preview
 PDF. Filename: Robust_Adaptive_Estimators_for_Nonlinear_Systems_final.pdf
Accepted Author Manuscript
Download (928kB)| Preview

Abstract

This paper is concerned with the development of new adaptive nonlinear estimators which incorporate adaptive estimation techniques for system noise statistics with the robust technique. These include Extended H∞ Filter (EHF), State Dependent H∞ Filter (SDHF) and Unscented H∞ Filter (UHF). The new filters are aimed at compensating the nonlinear dynamics as well as the system modeling errors by adaptively estimating the noise statistics and unknown parameters. For comparison purposes, this adaptive technique has also being applied to the Kalman-based filter which include extended Kalman filter (EKF), state dependent Kalman filter (SDKF) and Unscented Kalman filter (UKF). The performance of the proposed estimators is demonstrated using a two-state Van der Pol oscillator as a simulation example.

ORCID iDs

Abdul Wahab, Hamimi Fadziati Binti ORCID logoORCID: https://orcid.org/0000-0002-2610-9181 and Katebi, Reza ORCID logoORCID: https://orcid.org/0000-0003-2729-0688;
CORE (COnnecting REpositories)