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JOURNALS // Informatika i Ee Primeneniya [Informatics and its Applications] // Archive

Inform. Primen., 2018 Volume 12, Issue 3, Pages 99–106 (Mi ia553)

This article is cited in 7 papers

Stochastic differential system output control by the quadratic criterion. I. Dynamic programming optimal solution

A. V. Bosov, A. I. Stefanovich

Institute of Informatics Problems, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation

Abstract: The problem of optimal control for the Ito diffusion process and a controlled linear output is solved. The considered statement is close to the classical linear-quadratic Gaussian control (LQG control) problem. Differences consist in the fact that the state is described by the nonlinear differential Ito equation $dy_y = A_t(y_t) \,dt+\Sigma_t(y_t)\,dv_t$ and does not depend on the control $u_t$, optimization subject is controlled linear output $dz_t=a_ty_t\,dt +b_tz_t\,dt +c_t u_t\,dt +\sigma_t \,dw_t$. Additional generalizations are included in the quadratic quality criterion for the purpose of statement such problems as state tracking by output or a linear combination of state and output tracking by control. The method of dynamic programming is used for the solution. The assumption about Bellman function in the form $V_t(y,z)= \alpha_t z^2+\beta_t(y) z+\gamma_t(y)$ allows one to find it. Three differential equations for the coefficients $\alpha_t$, $\beta_t(y)$, and $\gamma_t(y)$ give the solution. These equations constitute the optimal solution of the problem under consideration.

Keywords: stochastic differential equation; optimal control; dynamic programming; Bellman function; Riccati equation; linear differential equations of parabolic type.

Received: 30.03.2018

DOI: 10.14357/19922264180314



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