Risk-Averse Control of Weakly Coupled Bilinear Stochastic Systems

Khanh D. Pham
Additional contact information
Khanh D. Pham: Space Vehicles Directorate

Chapter Chapter 6 in Resilient Controls for Ordering Uncertain Prospects, 2014, pp 101-123 from Springer

Abstract: Abstract The chapter treats the problem of controlling weakly coupled bilinear stochastic systems with quadratic criteria, including sensitivity variables is investigated, when noisy measurements are available. As expected, the procedural mechanism involves a Kalman-like estimator for the system state estimates. Furthermore, the risk-averse control parameters are enabled by the sets of backward-in-time matrix and vector differential equations, whose solutions are then committed as the appropriate statistical measures of performance expectation and risks; e.g., mean, variance, skewness, etc. Generally, these mathematical statistics now serve not only as feedback information for future risk-averse decisions and but also as an influence mechanism for the low sensitivity controller.

Keywords: System State Estimation; Performance-measure Statistics; Operational Risk Measurement; Cumulant-generating Function; Trajectory Sensitivity (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-319-08705-4_6

Ordering information: This item can be ordered from
http://www.springer.com/9783319087054

DOI: 10.1007/978-3-319-08705-4_6

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().