Simulation of a Two-level Control System for Nonlinear Dynamic Objects with a Neurofuzzy Adaptive Regulator

The article deals with the construction of a two-level control system for dynamic objects with nonlinear properties, functioning under conditions of a priori uncertainty. The lower level of control includes local controllers that provide the closed-loop system with parametric invariance to variations in the parameters of the object and compensate for the effects of external and internal disturbances. For the upper control level, it is proposed to apply control algorithms based on methods of fuzzy logic and neural networks. A comparative analysis of the results obtained with the classical adaptive controller is carried out.