Approximation and optimality necessary conditions in relaxed stochastic control problems.
Approximation approach for nonlinear filtering problem with time dependent noises. I. Conditionally optimal filter in the minimum mean square sense
Approximation approach for nonlinear filtering problem with time dependent noises. II. Stable nonlinear filters
Approximation, estimation and control of stochastic systems under a randomized discounted cost criterion
The paper deals with a class of discrete-time stochastic control processes under a discounted optimality criterion with random discount rate, and possibly unbounded costs. The state process and the discount process evolve according to the coupled difference equations
Approximation numérique d'une inéquation quasi variationnelle liée à des problèmes de gestion de stock
Approximation of the Zakai equation in a nonlinear filtering problem with delay
A nonlinear filtering problem with delays in the state and observation equations is considered. The unnormalized conditional probability density of the filtered diffusion process satisfies the so-called Zakai equation and solves the nonlinear filtering problem. We examine the solution of the Zakai equation using an approximation result. Our theoretical deliberations are illustrated by a numerical example.
Assets/liabilities portfolio immunization as an optimization problem
Assumption evaluation in approximate modelling
Asymmetric recursive methods for time series
The problem of asymmetry appears in various aspects of time series modelling. Typical examples are asymmetric time series, asymmetric error distributions and asymmetric loss functions in estimating and predicting. The paper deals with asymmetric modifications of some recursive time series methods including Kalman filtering, exponential smoothing and recursive treatment of Box-Jenkins models.
Asymptotic properties and optimization of some non-Markovian stochastic processes
We study the limit behavior of certain classes of dependent random sequences (processes) which do not possess the Markov property. Assuming these processes depend on a control parameter we show that the optimization of the control can be reduced to a problem of nonlinear optimization. Under certain hypotheses we establish the stability of such optimization problems.
Asymptotic results in parameter estimation for Gibbs random fields
Asymptotic stability condition for stochastic Markovian systems of differential equations
Asymptotic stability of the zero solution for stochastic jump parameter systems of differential equations given by , where is a finite-valued Markov process and w(t) is a standard Wiener process, is considered. It is proved that the existence of a unique positive solution of the system of coupled Lyapunov matrix equations derived in the paper is a necessary asymptotic stability condition.
Asymptotic stability, ergodicity and other asymptotic properties of the nonlinear filter
Asymptotical mean square stability of Cohen-Grossberg neural networks with random delay.
Asymptotically optimal filtering in linear systems with fractional Brownian noises.
In this paper, the filtering problem is revisited in the basic Gaussian homogeneous linear system driven by fractional Brownian motions. We exhibit a simple approximate filter which is asymptotically optimal in the sense that, when the observation time tends to infinity, the variance of the corresponding filtering error converges to the same limit as for the exact optimal filter.
Asymptotics of utility from terminal wealth for partially observed portfolios
We study the asymptotical behaviour of expected utility from terminal wealth on a market in which asset prices depend on economic factors that are unobserved or observed with delay.
Asynchronous distributed state estimation for continuous-time stochastic processes
The problem of state estimation of a continuous-time stochastic process using an Asynchronous Distributed multi-sensor Estimation (ADE) system is considered. The state of a process of interest is estimated by a group of local estimators constituting the proposed ADE system. Each estimator is based, e.g., on a Kalman filter and performs single sensor filtration and fusion of its local results with the results from other/remote processors to compute possibly the best state estimates. In performing...
Attainability analysis in the problem of stochastic equilibria synthesis for nonlinear discrete systems
A nonlinear discrete-time control system forced by stochastic disturbances is considered. We study the problem of synthesis of the regulator which stabilizes an equilibrium of the deterministic system and provides required scattering of random states near this equilibrium for the corresponding stochastic system. Our approach is based on the stochastic sensitivity functions technique. The necessary and important part of the examined control problem is an analysis of attainability. For 2D systems,...
Attitude observer-based robust control for a twin rotor system
In this paper, an angular tracking control based on adaptive super twisting algorithm (ASTA) for a Twin Rotor System is presented. With the aim of implementing the ASTA control and taking into consideration the difficulties of measuring some of its states, a Nonlinear Extended State Observer (NESO) is employed to estimate the vector state and furthermore unmeasured dynamics. This scheme increases robustness against unmodeled dynamics and external disturbance, reducing modeling difficulties due to...
Automatic stochastic control of impulses on a three-dimensional crystallographic lattice