Year: 2013
Type: preprint
Abstract: This paper derives recursion equations for a robust smoothing problem for a class of nonlinear systems with uncertainties in modeling and exogenous noise sources. The systems considered operate in discrete-time and the uncertainties are modeled in terms of a sum quadratic constraint. The robust smoothing problem is solved in terms of a forward-time and a reverse-time filter. Both these filters are formulated in terms of set-valued state estimators and are recast into subsidiary optimal control problems. These optimal control problems are described in terms of discrete-time Hamilton-Jacobi-Bellman equations, whose approximate solutions lead to recursive Riccati difference equations, filter state equations, and level shift scalar equations for the forward-time and the reverse-time filters.
Source: arXiv (Cornell University)
Authors: Kallapur, Abhijit G., Petersen, Ian R.
Institutions: Australian Defence Force Academy, UNSW Canberra
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2952509186