Mathematical modeling with uncertainty in microelectronics

The necessity of mathematical modeling with uncertainty for processes and systems in microelectronics is discussed. In such modeling, in fact, evolution of attainable sets of the systems is considered. The cost of such transition to simulation with uncertainty is the increase in mathematics complexity under use. Two examples are considered: etching and deposition simulation; logic simulation for digital circuits.

Fuzzy mamdani logic inference model in the loading of distribution substation transformer SCADA system

<span id="docs-internal-guid-152e332e-7fff-7073-a541-1d420decb47b"><span>The research objective of supervisory control and data acquisition (SCADA), with fuzzy Mamdani logic simulation on the loading section of distribution transformer substations. Data acquisition is available when saving SAIFI SAIDI data and storing the results of monitoring equipment. The method used is Mamdani fuzzy logic, there are two input variables, namely current and voltage devices. The membership function in Mamdani fuzzy logic has been created based on the input current and voltage variables. Currently: parameter {0, 600} low is created {0, 350, 450, 600}, normal {400-650} parameter is created {400, 500, 550, 650}, parameter high {≥600} is created {600, 650, 750, 1000}, when determining the voltage: low {≤10.5} parameters {0 4 7 10.5}, normal {9-14} parameters {9, 10, 13, 14} and high {≥13} - parameters {13, 14, 15, 16}. Based on the results of the Mamdani logic rule test on the output current containing a transformer and a voltage sensor, the results obtained are IF (normal current; (630) AND voltage (high); (13.2) (high load transformer). The components in the simulation tool include miniature substations made with the 1A travel substation model, 3A substation as the main substation, the relay as distribution substation as the monitoring application. Telestatus and Telecontrol use a microcontroller. Initial scenario. After substation is resumed, data is stored after downtime, service life, duration, and data period. Initial scenario After substation is resumed, data is stored after downtime, service life, duration, and data period.</span></span>

Fuzzy logic simulation of oat yield after using hydrogel and nitrogen biopolymer management

The fuzzy logic is an efficient tool for simulation and validation of new technologies in agriculture. The objective of the study is to adapt the fuzzy logic model for simulation of biomass and oat grain yield by nitrogen involving the nonlinearity of the maximum air temperature in the conditions of use of the biopolymer hydrogel, considering high succession systems and low release of residual N. The study was conducted in 2014 and 2015, in a randomized block design with four replicates in a 5 x 5 factorial. Five hydrogel doses (0, 30, 60, 90 and 120 kg ha-1) were added in the groove next to the seed; and 5 doses of N-fertilizer (0, 30, 60, 90 and 120 kg ha-1) applied at the fourth expanded leaf stage, respectively. The cultivar was URS Corona. The pertinence functions and the linguistic values established in the input and output variables to simulate the biomass yield and oat grains in the succession systems are adequate observed productivity. The fuzzy model makes it possible to estimate the biomass and oat grains productivity efficiently under the conditions of use of the hydrogel as a function of the nitrogen doses and maximum air temperature, adding to the existing models of simulation.

AN APPROACH TO SOLVE THE PROBLEM OF DATA FUSION FOR MULTI-TARGET TRACKING USING FUZZY LOGIC

This paper presents a multitarget data fusion (identification) algorithm called the Fuzzy data fusion algorithm (FDFA) for radar target tracking. This approach is formulated using the Kalman filter and FDF, the algorithm is accomplished by using fuzzy logic. Simulation results for cluttered conditions show that the proposed algorithm's performance is better than the probability data fusion (PDF) and the joint probability data fusion (JPDF) filters, which were presented in [2-4, 6].