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- W2167446990 abstract "Control design for stochastic systems is traditionally based on optimization of the expected value of a suitably chosen loss function. Despite the theoretical attractiveness of such a design methodology, its applicability is very limited owing to its computational overhead. Thus it is worthwhile to seek an alternative formulation resulting in a more tractable design. In this paper, an alternative is presented that leads to a simpler form of design equations. The proposed controller minimizes the Kullback-Leibler distance between the actual probabilistic descriptions of the closed-loop behaviour and the desired one. Its explicit randomized form depends on the solution of a functional equation with a simpler structure than that of the general dynamic programming equations. A basic paradigm is proposed, and the resulting algorithm is discussed. For illustration purposes, it is applied to linear Gaussian systems, and the desired result is obtained: The optimal controller is determined by a discrete-time Riccati equation." @default.
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- W2167446990 date "1996-12-01" @default.
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- W2167446990 title "Towards fully probabilistic control design" @default.
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- W2167446990 doi "https://doi.org/10.1016/s0005-1098(96)80009-4" @default.
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