arXiv · 2303.10293
Covariance Steering for Systems Subject to Unknown Parameters
Abstract
This work considers the optimal covariance steering problem for systems subject to both additive noise and uncertain parameters which may enter multiplicatively with the state and the control. The unknown parameters are modeled as a constant random variable sampled from a distribution with known moments. The optimal covariance steering problem is formulated using a moment-based representation of the system dynamics, which includes dependence between the unknown parameters and future states, and is solved using sequential convex programming. The proposed approach is demonstrated numerically using a holonomic spacecraft system and an autonomous vehicle control application.
Explore related subjects
Keep this discovery
Jacob Knaup, Panagiotis Tsiotras. 2023-03-18. Covariance Steering for Systems Subject to Unknown Parameters. https://arxiv.org/abs/2303.10293
Cite the original work for its findings. Save a collection to share your selection of sources.