Stochastic Linear Quadratic Optimal Control with Indefinite Control Weights and Constraint for Discrete-Time Systems

Xikui Liu, Guiling Li and Yan Li

Mathematical Problems in Engineering, 2015, vol. 2015, 1-11

Abstract:

The Karush-Kuhn-Tucker (KKT) theorem is used to study stochastic linear quadratic optimal control with terminal constraint for discrete-time systems, allowing the control weighting matrices in the cost to be indefinite. A generalized difference Riccati equation is derived, which is different from those without constraint case. It is proved that the well-posedness and the attainability of stochastic linear quadratic optimal control problem are equivalent. Moreover, an optimal control can be denoted by the solution of the generalized difference Riccati equation.

Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:476545

DOI: 10.1155/2015/476545

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