State Estimation for Nonlinear Discrete–time Fractional Systems: A Bayesian Perspective
Signal Processing（2019）CCF CSCI 2区
Univ Sci & Technol China
Abstract
In this paper, the state estimation issue for fractional dynamic systems is addressed. First, based on the Bayesian formula, a recursive Bayesian filter is derived from a probability density perspective. Then for a nonlinear fractional Gaussian system, a general fractional Gaussian filtering framework is investigated. Under this framework, the fractional particle filter is investigated systematically, and the working mechanism, time complexity and estimation accuracy of four suboptimal fractional filters are analyzed. Finally, several simulation examples verify the effectiveness of four suboptimal filters. (C) 2019 Elsevier B.V. All rights reserved.
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Key words
Fractional systems,Bayesian state estimation,Fractional Kalman filter,Fractional particle filter
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