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Stochastic Linear Quadratic Optimal Control with Indefinite Control Weights and Constraint for Discrete-Time Systems
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-01-22
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Liu, Xikui& Li, Guiling& Li, Yan. 2015. Stochastic Linear Quadratic Optimal Control with Indefinite Control Weights and Constraint for Discrete-Time Systems. Mathematical Problems in Engineering،Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073923
Modern Language Association (MLA)
Liu, Xikui…[et al.]. Stochastic Linear Quadratic Optimal Control with Indefinite Control Weights and Constraint for Discrete-Time Systems. Mathematical Problems in Engineering No. 2015 (2015), pp.1-11.
https://search.emarefa.net/detail/BIM-1073923
American Medical Association (AMA)
Liu, Xikui& Li, Guiling& Li, Yan. Stochastic Linear Quadratic Optimal Control with Indefinite Control Weights and Constraint for Discrete-Time Systems. Mathematical Problems in Engineering. 2015. Vol. 2015, no. 2015, pp.1-11.
https://search.emarefa.net/detail/BIM-1073923
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1073923