English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

In this paper, we present new results on the covariance steering problem withWasserstein distance terminal cost. We show that the state history feedbackcontrol policy parametrization, which has been used before to solve this classof problems, requires an unnecessarily large number of variables and can bereplaced by a randomized state feedback policy which leads to more tractableproblem formulations without any performance loss. In particular, we show thatunder the latter policy, the problem can be equivalently formulated as asemi-definite program (SDP) which is in sharp contrast with our previousresults that could only guarantee that the stochastic optimal control problemcan be reduced to a difference of convex functions program. Then, we show thatthe optimal policy that is found by solving the associated SDP corresponds to adeterministic state feedback policy. Finally, we present non-trivial numericalsimulations which show the benefits of our proposed randomized state feedbackpolicy derived from the SDP formulation of the problem over existing approachesin the field in terms of computational efficacy and controller performance.

Exact SDP Formulation for Discrete-Time Covariance Steering with Wasserstein Terminal Cost