Erratum of article “Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems”
Erratum of article “Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems”
Erratum of “The squares of the Laplacian-Dirichlet eigenfunctions are generically linearly independent”
Estimació del pol i de la variància del soroll d'un model AR (1) mitjançant filtratge no lineal.
La estimación de los parámetros asociados a un proceso ARMA puede plantearse como un problema de filtrado no lineal. Para determinar un estimador recursivo de estos parámetros se define un vector de estado ampliado que incluye las variables de estado y los parámetros a estimar. Con un enfoque bayesiano se determina la distribución a posteriori del vector de estado ampliado. La síntesis del filtro no lineal permite: i) estimar los parámetros y determinar su precisión para un tamaño de muestra dado,...
Estimación adaptativa en tiempo real de funciones de transferencia. Revisión de las técnicas disponibles y presentación de nuevos algoritmos.
En este artículo se analizan los problemas planteados en la estimación en tiempo real de los parámetros de sistemas variantes con el tiempo, con el objeto de definir los requisitos que debe verificar un estimador de este tipo. Seguidamente se realiza un análisis crítico de las técnicas de estimación adaptativa...
Estimates for perturbations of average Markov decision processes with a minimal state and upper bounded by stochastically ordered Markov chains
This paper deals with Markov decision processes (MDPs) with real state space for which its minimum is attained, and that are upper bounded by (uncontrolled) stochastically ordered (SO) Markov chains. We consider MDPs with (possibly) unbounded costs, and to evaluate the quality of each policy, we use the objective function known as the average cost. For this objective function we consider two Markov control models and . and have the same components except for the transition laws. The transition...
Estimates for perturbations of discounted Markov chains on general spaces
We analyse a Markov chain and perturbations of the transition probability and the one-step cost function (possibly unbounded) defined on it. Under certain conditions, of Lyapunov and Harris type, we obtain new estimates of the effects of such perturbations via an index of perturbations, defined as the difference of the total expected discounted costs between the original Markov chain and the perturbed one. We provide an example which illustrates our analysis.
Estimates of stability of Markov control processes with unbounded costs
For a discrete-time Markov control process with the transition probability , we compare the total discounted costs ...
Estimation and control in finite Markov decision processes with the average reward criterion
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 des paramètres dans le modèle linéaire général dynamique
Estimation for linear pure delay time systems
Estimation of feedwater heater parameters based on a grey-box approach
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 functions of a dependent variable
Estimation of hidden Markov models for a partially observed risk sensitive control problem
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 polynomial roots by continued fractions
Estimation of the output deviation norm for uncertain, discrete-time nonlinear systems in a state dependent form
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...
Estimation of tolerance relation on the basis of multiple pairwise comparisons with random errors
Estimation récursive des paramètres d'un modèle de régression, variant au cours du temps
Estimation semi-paramétrique d'un modèle autorégressif stationnaire multiindice non nécessairement causal
Estrategias óptimas de publicidad y precio.
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.