Paper Details: Downloads: 826
Serial Number: P1111130668
Title: Qualitative State Estimation from corrupted Data with Uncertain Parameters
Authors: Mohamed F. Hassan and Hala A. Mourad
Abstract: In this paper, an estimator is developed to estimate the states of linear stochastic discrete-time dynamical systems with uncertain parameters. The system model and the measurements are assumed to be corrupted by uncorrelated zero mean white Gaussian noise sequences. The parameters of the system are assumed to be uncertain. The proposed approach is based on Kalman filter. Although the developed state estimator uses the nominal values of the system parameters; it showed to be stable, robust and gives satisfactory results. The effectiveness of the theoretical derivation of the developed estimator is illustrated via simulation examples and a real DC Motor application.
Keywords: Discrete-time systems, linear systems, nonlinear systems, stability, state estimation, stochastic systems.
Journal/Conference: ICGST Conference on Computer Science and Engineering, CSE-11
Volume:
Issue:
Submission Date: 7/26/2011 12:00:00 AM
Review Date: 11/22/2011 12:00:00 AM
Publishing Date: 12/19/2011 12:00:00 AM
Article Downloads: 826
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