Paper Info
Title
Risk-sensitive control and dynamic games for partially observed discrete-time nonlinear systems
Abstract
Solves a finite-horizon partially observed risk-sensitive stochastic optimal control problem for discrete-time nonlinear systems and obtains small noise and small risk limits. The small noise limit is interpreted as a deterministic partially observed dynamic game, and new insights into the optimal solution of such game problems are obtained. Both the risk-sensitive stochastic control problem and the deterministic dynamic game problem are solved using information states, dynamic programming, and associated separated policies. A certainty equivalence principle is also discussed. The authors' results have implications for the nonlinear robust stabilization problem. The small risk limit is a standard partially observed risk-neutral stochastic optimal control problem.
Year
DOI
Venue
1994
10.1109/9.286253
Automatic Control, IEEE Transactions  
Keywords
DocType
Volume
discrete time systems,dynamic programming,game theory,nonlinear control systems,optimal control,stability,state estimation,stochastic systems,certainty equivalence principle,deterministic partially observed dynamic game,dynamic programming,finite-horizon partially observed risk-sensitive stochastic optimal control problem,information states,nonlinear robust stabilization problem,partially observed discrete-time nonlinear systems,small noise limit,small risk limits,standard partially observed risk-neutral stochastic optimal control problem
Journal
39
Issue
ISSN
Citations 
4
0018-9286
68
PageRank 
References 
Authors
34.28
1
3
Name
Order
Citations
PageRank
James, M.R.16834.28
Baras, J.S.26834.28
Elliott, R.J.36834.28