Timofeyev V. Synthesis of adaptive critical control systems in conditions of uncertainty

Dissertation covers questions of studying and solution of the problem of adaptive critical control of dynamic non-stationary objects functioning in conditions of significant a priori and current uncertainty using learning models. Methods of critical control based on adaptive approach using adaptive identification contour in the critical system have been developed. This contour determines parameters of the model in real-time in conditions of a priori and current uncertainty related to the object parameters and environment properties. General structure of adaptive critical control rule has been proposed. Methods and models of adaptive critical identification and control have been created and optimization methods for appropriate regulators have been developed. The question of convergence for identification algorithms and durability for control algorithms of critical systems has been studied.