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Linear, nonlinear, modified, high-speed defuzzifiers based on the area ratio method are presented in this paper. The proposed defuzzifiers are used in a fuzzy digital filter device and make it possible to ensure the additivity of the robotic manipulator control system, since traditional models do not have this property. The essence of this development is to find a crisp value of the output fuzzy variable, which in this case are the regulation coefficients of the fuzzy digital filter. Reducing the number of computational operations provides an increase in the performance of the defuzzifier. The reduction in number of computational operations is carried out by eliminating the output variable’s truncated term’s height calculation, thereby reducing the computation time. A simulation model which was implemented in the MatLab Simulink system, for a neuro-fuzzy device of the robotic arm using linear and non-linear defuzzifiers is presented. The dependence of time graphs on the angle of rotation of the joints of the robotic manipulator are compared, based on the traditional center of gravity method and the method shown in this paper. It was found that the traditional center of gravity method does not ensure the fulfillment of the specified rotation angles of the links of the robotic arm, while the proposed models of defuzzifiers have this property, which can be seen from the presented dependency graphs. The simulation model of the device was also designed as a parallel-conveyor device for implementation in the field-programmable gate array of the Xilinx Spartan 3Е family. The analysis showed that the calculation time for a crisp value with high-speed defuzzification is 130 ns, which is two orders of magnitude higher than existing models. The experiment was conducted at a frequency of 100 MHz.

Purpose of reseach. Digital signal filtering allows real-time noise reduction in electronic devices. Currently, there are many different digital filters, differing in speed, computing power, algorithms and restrictions on the conditions of use. One of these filters is the Kalman filter, but adjusting the gains of this filter is very complicated by the process of additional experiments and collection of statistical information. Therefore, in this paper, the authors consider a simplified algorithm for finding the control coefficients of a fuzzy digital filter with defuzzifier based on the area ratio method and investigate the influence of the area ratio method parameters on signal filtering, thereby achieving the goal of improving the accuracy of the fuzzy digital filter. Methods. For the algorithm for finding the control coefficients of the digital filter, a fuzzy logic apparatus was used. The control factors are determined using a defuzzifier based on the area ratio method. Results. In the course of experimental studies, the mean square error RMSE was calculated for a fuzzy digital filter using the area ratio method, the center of gravity method and the Kalman filter. Based on the results obtained, it was concluded that the fuzzy filter based on the area ratio RMSE method is 5.43 times less than for the Kalman filter and 2.77 times less than for the defuzzifier based on the center of gravity method. The results obtained prove the effectiveness of using a fuzzy digital filter with the area ratio method. Conclusion: This article considers an algorithm for the operation of a fuzzy digital filter, simulates a fuzzy digital filter and a Kalman filter in the Simulink system and calculates the RMSE values for a fuzzy digital filter with the area ratio method and the center of gravity method, as well as the Kalman filter.