No abstract

The accurate measurement of RMS values of voltage and current is crucial for the monitoring and protection of power systems and in general for electrical power distribution systems. The authors in this paper have developed an algorithm to calculate the RMS value of sinusoidal signals of varying frequency, by applying phasors obtained from digital filters SAL and CAL. In conditions in which the frequency of the grid varies, a phase shift is presented in the phasor of the grid voltage which is used for the design of a regulator that allows to obtain accurate RMS voltage values. The choice of the SAL and CAL digital filters is due to their low computational requirement, so they can be implemented in general-purpose microcontrollers.

No abstract

In this work, the AutonomousSystems4D package is presented, which allows the qualitative analysis of non-linear differential equation systems in four dimensions, as well as drawing the phase surfaces by immersing R4 in R3. The package is programmed in the computational tool Octave. As a case study applied to the new Lorenz 4D System, sensitivity was found in the initial conditions, Lyapunov exponents, Kaplan Yorke dimension, a stable and unstable critical point, limit cycle, Hopf bifurcation, and hyperattractors. The package could be adapted to perform qualitative analysis and visualize phase surfaces to autonomous systems, e.g. Sprott 4D, Rossler 4D, etc. The package can be applied to problems such as: design, analysis, implementation of electronic circuits; to message encryption.

In this work, a fuzzy linear equation AX + B = 0, is solved, were A, B y C are triangular diffuse numbers, could also be trapezoidal. For this type of equations there are several solution methods, the classic method that does not always obtain solutions, the most used is the method of alpha cuts and arithmetic intervals that although it always finds a solution, as a value is taken closer to zero (more inaccurate), the solution satisfies less to the equation. The new method using the expected interval, allows to obtain a smaller support set where the solutions come closer to satisfying the equation, also allows to find a single interval where the best solutions for decision making are expected to be found. It is recommended to study the incorporation of the concept of the expected interval in the methods to solve systems of fuzzy linear equations