Dynamic reconstruction of controls under uncertainty conditions

The problem of the dynamic reconstruction of a priori unknown controls or parameters of a dynamical system is considered. This reconstruction is based on the results of observation of the evolution of certain informative sets containing a priori unknown current state values of the system. Noise-supressing dynamic algorithms for solving the problem are constructed. These algorithms are physically realizable and can work in the on-line mode. The construction is based on the methods of the theory of feedback control.