Browsing by Subject "Partial differential equations"
Now showing items 112 of 12

Conference Object
Applications of minimum principle for continuoustime partially observable risksensitive control problems
(IEEE, 1995)This paper employs the minimum principle derived in [1], for nonlinear partially observable exponential of integral control problems, to solve linearexponentialquadraticGaussian (LEQG) tracking problems using two different ...

Conference Object
Certain results concerning filtering and control of diffusions in small white noise
(IEEE, 1997)The purpose of this talk is twofold. First, we examine in detail the binary hypothesis decision and/or estimation problem using a risksensitive cost criterion, when the state and observation processes are diffusion signals. ...

Article
Conditional densities for continuoustime nonlinear hybrid systems with applications to fault detection
(1998)Continuoustime nonlinear stochastic differential state and measurement equations, all of which have coefficients capable of abrupt changes at a random time, are considered; finitestate jump Markov chains are used to model ...

Article
Conditional densities for continuoustime nonlinear hybrid systems with applications to fault detection
(1999)Continuoustime nonlinear stochastic differential state and measurement equations, all of which have coefficients capable of abrupt changes at a random time, are considered; finitestate jump Markov chains are used to model ...

Conference Object
Conditional moment generating functions for integrals and stochastic integrals
(IEEE, 1997)In this paper we present two methods for computing filtered estimates for moments of integrals and stochastic integrals of continuoustime nonlinear systems. The first method utilizes recursive stochastic partial differential ...

Conference Object
Evaluation of likelihoodratio and performance bounds for nonlinear decision problems via stochastic PDE
(American Automatic Control Council, 1994)The nonlinear binary decision problem with signal satisfying a diffusion equation observed through noisy measurements is considered. Using the unnormalized conditional density of nonlinear filtering, expressions for ...

Article
Finitedimensional nonlinear output feedback dynamic games and bounds for sector nonlinearities
(1999)In general, nonlinear output feedback dynamic games are infinitedimensional. This paper treats a class of minimax games when the nonlinearities enter the dynamics of the unobservable states. An information state approach ...

Conference Object
Information states in optimal control of stochastic systems: A Lie algebraic theoretic approach
(IEEE, 1997)In this paper we introduce the sufficient statistic algebra which is responsible for propagating the sufficient statistic, or information state, in the optimal control of stochastic systems. Using a Lie algebraic formulation, ...

Article
Necessary conditions of optimization for partially observed controlled diffusions
(1999)Necessary conditions are derived for stochastic partially observed control problems when the control enters the drift coefficient and correlation between signal and observation noise is allowed. The problem is formulated ...

Article
Quadratic forms for FeynmanKac semigroups
(2006)Some problems in a stochastic setting often involve the need to evaluate the FeynmanKac formula that follows from models described in terms of stochastic differential equations. Equivalent representations in terms of ...

Conference Object
Remarks on the explicit solutions for nonlinear partially observable stochastic control problems and relations to H∞ or robust control
(IEEE, 1995)Partially observable stochastic and H∞ control problems are considered. The dynamics include nonlinearities which are the gradient of some potential function in addition to linear terms, the observations are linear, and ...

Conference Object
Stochastic nonlinear minimax dynamic games with noisy measurements
(IEEE, 1999)This paper is concerned with nonlinear stochastic minimax dynamic games which are subject to noisy measurements. The minimizing players are control inputs while the maximizing players are squareintegrable stochastic ...