Multiparameter control modeling of electrical signal in a medium voltage network by Markov random approach

Abstract

In this paper, the electrical signals coupled to the fields present in a medium voltage network are analyzed by the random
Markov approach. This approach with the contribution of the “Yakam Matrix” is studied to establish the quantitative approximations
of the current I and the voltage V in non-steady state conditions in order to efficiently deduct the error percent between the
experimental and the simulated results. Also, the aim was to determine the functional constant with infinite duration through multivariable
stabilization in commandability and controllability process. The development of the transition and observability matrices of
the electrical signals behavior to establish the initialization’s system of Dirichlet is presented where the vector  by the hidden Markov
approach revealed to be almost stable. The multiparameter analysis in non-steady state conditions is conducted to show the maximum
probability of the injected signals. The comparison of the experimental results with the simulation is presented with a 4% error
obtained by using MATLAB. Since the function current I(t) remains in (0  I  20)A conditions in case of phase disconnection.
However, the application of the Markov random approach in electrical networks control modeling still require further studies and
clarifications.