Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
752576 | Systems & Control Letters | 2006 | 7 Pages |
Abstract
Stochastic control design chooses the controller that makes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design describes both the closed loop and its desired behavior in probabilistic terms and uses Kullback–Leibler divergence as their proximity measure. This approach: (i) unifies stochastic control design methodology; (ii) provides explicit minimizer.The paper completes the previous solutions of various particular cases by formulating and solving the fully probabilistic control design in the general, discrete-time, state-space setting.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Miroslav Kárný, Tatiana V. Guy,