Non-Gaussian filter based on the Method of Characteristics for Nonlinear Dynamical Systems Conference Paper

abstract

• 2019 American Automatic Control Council. This paper deals with the development of a non-Gaussian filter for nonlinear systems with discrete time measurements. Specifically, for systems with no process noise, the evolution of the state probability density function is governed by the Liouville equation. In general, solving the Liouville equation is computationally challenging. To this end, we leverage the method of characteristics to propagate probabilities along the characteristics solutions of the Liouville equation. Further, a convex optimization procedure is proposed to reconstruct the state probability density function from these characteristic solutions. Numerical examples of capturing the non-Gaussian nature of the uncertainty in the duffing oscillator and the two body problem are illustrated.

name of conference

• 2019 American Control Conference (ACC)

authors

• Majji, Manoranjan

published proceedings

• 2019 AMERICAN CONTROL CONFERENCE (ACC)

author list (cited authors)

• Adurthi, N., & Majji, M.

citation count

• 1

complete list of authors

• Adurthi, Nagavenkat||Majji, Manoranjan

publication date

• January 2019

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings of the ... American Control Conference. American Control Conference  Journal

keywords

• Characteristic Solutions
• Convex Optimization Procedure
• Convex Programming
• Discrete Time Measurements
• Discrete Time Systems
• Duffing Oscillator
• Filtering Theory
• Gaussian Processes
• Liouville Equation
• Nongaussian Filter
• Nonlinear Dynamical Systems
• Probability
• State Probability Density Function
• Two Body Problem

Digital Object Identifier (DOI)

• 10.23919/acc.2019.8814812

International Standard Book Number (ISBN) 13

• 9781538679265

start page

• 2440

end page

• 2445

volume

• 2019-July

URL

• http://dx.doi.org/10.23919/acc.2019.8814812