Cumulants in risk-sensitive control: the full-state-feedback cost variance case

Michael K. Sain, Chang Hee Won, B F Spencer

Research output: Contribution to journalConference articlepeer-review

Abstract

The risk-sensitive optimal stochastic control problem has an interpretation in terms of managing the value of a denumerable linear combination of the cumulants of a traditional performance index. This paper considers in detail the foundations for a full-state-feedback solution to the problem of controlling the second cumulant of a cost function, given modest constraints on the first cumulant. The formulation is carried out for a class of nonlinear stochastic differential equations, associated with an appropriate class of non-quadratic performance indices. A Hamilton-Jacobi framework is adopted, and the defining equations for solving the linear, quadratic case are determined. The method is then applied to a situation in which a building is to be protected from earthquakes.

Original languageEnglish (US)
Pages (from-to)1036-1041
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
StatePublished - Dec 1 1995
Externally publishedYes
EventProceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) - New Orleans, LA, USA
Duration: Dec 13 1995Dec 15 1995

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

Fingerprint Dive into the research topics of 'Cumulants in risk-sensitive control: the full-state-feedback cost variance case'. Together they form a unique fingerprint.

Cite this