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Estimation and control in finite Markov decision processes with the average reward criterion

Rolando Cavazos-Cadena, Raúl Montes-de-Oca (2004)

Applicationes Mathematicae

This work concerns Markov decision chains with finite state and action sets. The transition law satisfies the simultaneous Doeblin condition but is unknown to the controller, and the problem of determining an optimal adaptive policy with respect to the average reward criterion is addressed. A subset of policies is identified so that, when the system evolves under a policy in that class, the frequency estimators of the transition law are consistent on an essential set of admissible state-action pairs,...

Estimation of feedwater heater parameters based on a grey-box approach

Tomasz Barszcz, Piotr Czop (2011)

International Journal of Applied Mathematics and Computer Science

The first-principle modeling of a feedwater heater operating in a coal-fired power unit is presented, along with a theoretical discussion concerning its structural simplifications, parameter estimation, and dynamical validation. The model is a part of the component library of modeling environments, called the Virtual Power Plant (VPP). The main purpose of the VPP is simulation of power generation installations intended for early warning diagnostic applications. The model was developed in the Matlab/Simulink...

Estimation of hidden Markov models for a partially observed risk sensitive control problem

Bernard Frankpitt, John S. Baras (1998)

Kybernetika

This paper provides a summary of our recent work on the problem of combined estimation and control of systems described by finite state, hidden Markov models. We establish the stochastic framework for the problem, formulate a separated control policy with risk-sensitive cost functional, describe an estimation scheme for the parameters of the hidden Markov model that describes the plant, and finally indicate how the combined estimation and control problem can be re-formulated in a framework that...

Estimation of the output deviation norm for uncertain, discrete-time nonlinear systems in a state dependent form

Przemysław Orłowski (2007)

International Journal of Applied Mathematics and Computer Science

Numerical evaluation of the optimal nonlinear robust control requires estimating the impact of parameter uncertainties on the system output. The main goal of the paper is to propose a method for estimating the norm of an output trajectory deviation from the nominal trajectory for nonlinear uncertain, discrete-time systems. The measure of the deviation allows us to evaluate the robustness of any designed controller. The first part of the paper concerns uncertainty modelling for nonlinear systems...

Estrategias óptimas de publicidad y precio.

María del Carmen Castrodeza Chamorro, Rafael Caballero Fernández, Trinidad Gómez Núñez (1991)

Trabajos de Investigación Operativa

El modelo de control óptimo no lineal, considerado en este artículo, posee una variable de estado x proporción de clientes y dos variables de control: precio p y gastos en publicidad u. Realizando un análisis de estabilidad en diferentes planos de fase se demuestra, bajo ciertas hipótesis, que es óptimo introducir un producto en el mercado con un precio reducido y realizando una fuerte inversión al comienzo de la campaña.

Evaluating the Kernighan-Lin heuristic for hardware/software partitioning

Zoltán Mann, András Orbán, Viktor Farkas (2007)

International Journal of Applied Mathematics and Computer Science

In recent years, several heuristics have been proposed for the hardware/software partitioning problem. One of the most promising directions is the adaptation of the Kernighan-Lin algorithm. The Kernighan-Lin heuristic was originally developed for circuit partitioning, but it has been adapted to other domains as well. Moreover, numerous improvements have been suggested so that now several variants of the original algorithm exist. The aim of this paper is to systematically evaluate the possibilities...

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