Convergence Analysis for an Online Data-Driven Feedback Control Algorithm

Author:

Liang Siming1ORCID,Sun Hui2,Archibald Richard3ORCID,Bao Feng1

Affiliation:

1. Department of Mathematics, Florida State University, Tallahassee, FL 32304, USA

2. Citigroup Inc., Wilmington, DE 19801, USA

3. Devision of Computational Science and Mathematics, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USA

Abstract

This paper presents convergence analysis of a novel data-driven feedback control algorithm designed for generating online controls based on partial noisy observational data. The algorithm comprises a particle filter-enabled state estimation component, estimating the controlled system’s state via indirect observations, alongside an efficient stochastic maximum principle-type optimal control solver. By integrating weak convergence techniques for the particle filter with convergence analysis for the stochastic maximum principle control solver, we derive a weak convergence result for the optimization procedure in search of optimal data-driven feedback control. Numerical experiments are performed to validate the theoretical findings.

Funder

U.S. Department of Energy through FASTMath Institute and Office of Science

U.S. National Science Foundation

Publisher

MDPI AG

Reference22 articles.

1. An efficient numerical algorithm for solving data driven feedback control problems;Archibald;J. Sci. Comput.,2020

2. Dynamic programming;Bellman;Science,1966

3. Recent developments in numerical methods for fully nonlinear second order partial differential equations;Feng;SIAM Rev.,2013

4. A general stochastic maximum principle for optimal control problems;Peng;SIAM J. Control Optim.,1990

5. Yong, J., and Zhou, X.Y. (2012). Stochastic Controls: Hamiltonian Systems and HJB Equations, Springer Science & Business Media.

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