An algorithmic synthesis of discrete optimal singular adaptive observers for multiple-input single-output linear systems

An algorithmic synthesis of a new generation of discrete adaptive observers, including optimal estimators of the initial state vector, identifiers of parameters and discrete optimal singular (full and degenerate) adaptive observers of the current state vector for multiple-input single-output linear discrete systems is suggested. The estimation of the initial state vector elements is not typical of the methods for synthesis of discrete adaptive observers, based only on identifiers. The synthesized algorithm has features such as large-scale granularity and natural parallelism, which also allow its software and hardware implementation on a parallel computer architecture.