Nonlinear Covariance Control via Differential Dynamic Programming

We consider covariance control problems for nonlinear stochastic systems. Our objective is to find an optimal control strategy to steer the state from an initial distribution to a terminal one with specified mean and covariance. This problem is considerably more complicated than previous studies on...

Full description

Saved in:
Bibliographic Details
Main Authors Yi, Zeji, Cao, Zhefeng, Theodorou, Evangelos, Chen, Yongxin
Format Journal Article
LanguageEnglish
Published 20.11.2019
Subjects
Computer Science - Systems and Control
Online AccessGet full text

Cover

More Information
Summary:We consider covariance control problems for nonlinear stochastic systems. Our objective is to find an optimal control strategy to steer the state from an initial distribution to a terminal one with specified mean and covariance. This problem is considerably more complicated than previous studies on covariance control for linear systems. We leverage a widely used technique - differential dynamic programming - in nonlinear optimal control to achieve our goal. In particular, we adopt the stochastic differential dynamic programming framework to handle the stochastic dynamics. Additionally, to enforce the terminal statistical constraints, we construct a Lagrangian and apply a primal-dual type algorithm. Several examples are presented to demonstrate the effectiveness of our framework.
DOI:10.48550/arxiv.1911.09283