Synthesis of Multi-model Algorithms for Intelligent Estimation of Motion Parameters Under Conditions of Uncertainty Using Condition of Generalized Power Function Maximum and Fuzzy Logic

摘要

The article considers the problems relating the estimation of the motion parameters under conditions of uncertainty, which are caused by the lack of a priori information about the nature of the movement of the controlled object. Using traditional kinematic models may lead to divergence of the estimation process and failure of the computational procedure. The article shows that the constructive results of the synthesis of 2D dynamic models in the polar coordinate system can be provided using the maximum condition for the function of generalized power. Adaptation of the obtained models to different modes of motion is carried out using fuzzy logic. The constructiveness of the approach is confirmed by a comparative analysis of the results of mathematical modeling.