This paper presents an application of a modern numerical algorithm, namely probabilistic networks, for decision support in power system analysis. The method is illustrated by a problem involving detection of small leaks in a high-pressure, fluid-filled (HPFF) pipe type cable. The construction of...

This paper describes a design for a least mean square error estimator in discrete time systems where the components of the state vector, in measurement equation, are corrupted by different multiplicative noises in addition to observation noise. We show how known results can be considered a...

A design and utilization of a mathematical model of the contribution defined pension fund is treated. The mathematical model respects the specific character and economical rules of supplementary pension system in the Czech Republic. The state of the new mathematical model is partly immeasurable....

Lately, several approaches to state estimation and parameter change detection based on the utilization of a finite number of process models appeared. The paper compares these methods in a unified Bayesian framework.

The Lagrange multiplier-based method is an effective network parameter error identification method. However, two full matrices with high-dimensions are involved in the calculation procedure; these create huge computational burdens for large-scale power systems. To solve this problem, a fast...

Motion control of mobile robots and efficient trajectory tracking is usually based on prior estimation of the robots’ state vector. To this end Gaussian and nonparametric filters (state estimators from position measurements) have been developed. In this paper the Extended Kalman Filter which...

Software sensors (or state observers) are able to provide a continuous estimation of some signals (e.g. concentrations of important culture components, like biomass) which are not measured by hardware sensors. They need a mathematical model of the process and (discrete) hardware measurements of...

Renewable energy is energy that is in continuous supply over time. These kinds of energy sources are divided into five principal renewable sources of energy: the sun, the wind, flowing water, biomass and heat from within the earth. According to some studies carried out by the research...

This paper deals with the estimation of state changes in system descriptions for dynamic Bayesian networks (DBNs) by using a genetic procedure and particle filters (PFs). We extend the DBN scheme to more general cases with unknown Directed Acyclic Graph (DAG) and state changes. First, we...