Optimal transport over a linear dynamical system Journal Article


Authors: Chen, Y.; Georgiou, T. T.; Pavon, M.
Article Title: Optimal transport over a linear dynamical system
Abstract: We consider the problem of steering an initial probability density for the state vector of a linear system to a final one, in finite time, using minimum energy control. In the case where the dynamics correspond to an integrator (x(t) = u(t)) this amounts to a Monge-Kantorovich Optimal Mass Transport (OMT) problem. In general, we show that the problem can again be reduced to solving an OMT problem and that it has a unique solution. In parallel, we study the optimal steering of the state-density of a linear stochastic system with white noise disturbance; this is known to correspond to a Schrödinger bridge. As the white noise intensity tends to zero, the flow of densities converges to that of the deterministic dynamics and can serve as a way to compute the solution of its deterministic counterpart. The solution can be expressed in closed-form for Gaussian initial and final state densities in both cases. © 1963-2012 IEEE.
Keywords: problem solving; probability density function; stochastic systems; linear systems; linear control systems; optimal control; optimal mass transport; schrödinger bridges; stochastic linear systems; dynamical systems; stochastic control systems; white noise; linear dynamical systems; linear stochastic system; minimum energy control; optimal controls; optimal transport; probability densities
Journal Title: IEEE Transactions on Automatic Control
Volume: 62
Issue: 5
ISSN: 0018-9286
Publisher: IEEE  
Date Published: 2017-05-01
Start Page: 2137
End Page: 2152
Language: English
DOI: 10.1109/tac.2016.2602103
PROVIDER: scopus
DOI/URL:
Notes: Article -- Export Date: 2 June 2017 -- Source: Scopus
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  1. Yongxin Chen
    7 Chen