Covariance Steering With Optimal Risk Allocation

This article extends the optimal covariance steering (CS) problem for linear stochastic systems subject to chance constraints so as account an allocation of risk. Previous works have assumed a uniform risk in order cast control semidefinite program, which can be solved efficiently using standard SDP solvers. An iterative (IRA) formalism is used solve CS two-stage approach. The upper-stage IRA optimizes risk, convex problem, while lower-stage controller with new constraints. process applied iteratively until that achieves lowest total cost obtained. proposed framework results solutions tend maximize terminal covariance, still satisfying constraints, thus leading less conservative than previous methodologies. In this article, we consider both polyhedral and cone state Finally, demonstrate approach spacecraft rendezvous compare other competing approaches.