Brief paper: Risk-sensitivity conditions for stochastic uncertain model validation

Authors:
Valery Ugrinovskii
Affiliations:
School of Engineering and IT, University of New South Wales at the Australian Defence Force Academy, Canberra, ACT, 2600, Australia
Venue:
Automatica (Journal of IFAC)
Year:
2009

Citing 7
Cited 1

Stochastic realization problems

Three decades of mathematical system theory
Numerical methods for stochastic control problems in continuous time

Numerical methods for stochastic control problems in continuous time
Risk-Sensitive Control on an Infinite Time Horizon

SIAM Journal on Control and Optimization
Model validation for robust control of uncertain systems with an integral quadratic constraint

Automatica (Journal of IFAC)
Finite horizon minimax optimal control of nonlinear continuous time systems with stochastic uncertainty

Dynamics and Control
Minimax LQG Control of Stochastic Partially Observed Uncertain Systems

SIAM Journal on Control and Optimization
Equivalent realizations for uncertain systems with an IQC uncertainty description

Automatica (Journal of IFAC)

Towards a bridge between cost and wealth in risk-aware planning

Applied Intelligence

Quantified Score

Hi-index	22.14

Visualization

Abstract

The paper presents sufficient and necessary conditions that verify the relevance of an assumed linear stochastic system model for problems in which probabilistic characteristics of the plant are not known exactly. The approach is to establish the existence of an admissible probability space on which the output of the candidate stochastic system model is consistent (in a stochastic sense) with the noisy output of the plant.