Information-state approach to linear/risk-sensitive/quadratic/Gaussian control

Iain B. Collings*, Matthew R. James, John B. Moore

*Corresponding author for this work

Research output: Contribution to journalConference paperpeer-review

10 Citations (Scopus)


In this paper we use an information-state approach to obtain the solution to the linear risk-sensitive quadratic Gaussian control problem. With these methods the solution is obtained without appealing to a certainty equivalence principle. Specifically we consider the case of tracking a desired trajectory. The result gives some insight to more general information-state methods for non-linear systems. Limit results are presented which demonstrate the link to standard linear quadratic Gaussian control. Also, a risk-sensitive filtering result is presented which shows the relationship between tracking and filtering problems. Finally, simulation studies are presented to indicate some advantages gained via a risk-sensitive control approach.

Original languageEnglish
Pages (from-to)3802-3807
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Publication statusPublished - 1994
Externally publishedYes


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