Non-minimal Phase Systems in Adaptive Control Problems

The present paper describes the adaptive control synthesis for dynamic systems when the initial control is synthesized by the method of inverse problems of dynamics with linear type constraints. Due to the introduction of additional variables the initial closed control system is written in non-minimal phase form. The adaptation process is organized using the Lyapunov function in the extended state space. This space is formed by the errors vector equal to the difference between the values of the ideal and real processes, and by priori errors in determining the control object parameters. The use of non-minimal phase representation makes it possible to use not all components of the state vector of the initial control object, but only its controlled coordinates in adaptation algorithms.