Model reference adaptive control algorithms for decentralized systems

This paper presents two decentralized direct model reference adaptive control algorithms for large-scale interconnected systems having multi-input and multi-output subsystems and subjected to known disturbances. The parameters of each subsystem are assumed to be unknown constants taking values in a known bounded range. These algorithms do not require identification of the system parameters or satisfaction of the perfect model-following conditions. Applications to a power system example are presented to demonstrate the effectiveness of the proposed algorithms