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Joint state and parameter estimation based on constrained zonotopes
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DOI：10.1016/j.automatica.2022.110425.png)
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Abstract
En 中文
This note presents a new method for set-based joint state and parameter estimation of discrete-time systems using constrained zonotopes. This is done by extending previous set-based state estimation methods to include parameter identification in a unified framework. Unlike in interval-based methods, the existing dependencies between states and model parameters are maintained from one time step to the next, thus providing a more accurate estimation scheme. In addition, the enclosure of states and parameters is refined using measurements through generalized intersections, which are properly captured by constrained zonotopes. The advantages of the new approach are highlighted in two numerical examples. (C) 2022 Elsevier Ltd. All rights reserved.
Keywords:
Nonlinear state estimation
Parameter identification
Set-based computing
Constrained zonotopes
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