On-line parameter estimation and two-level control of large-scale discrete time systems

This paper introduces an new approach for parameter estimation and two-level control of large-scale discrete systems using input-output data. Parallel recursive least square estimation algorithms based on special observable canonical innovation model are considered and subsequently, parallel state estimation schemes are developed by partitioning the conventional Kalman-filter equation. Two-level controller is implemented by using estimated parameters. Global output feedback controller is designed to reduce the effect of state interaction between the subsystems and subsequently, a numerically reliable and stable local controller based on singular value decomposition (SVD) technique is considered to stabilize a'-d improve the performance of the composite system. Simulation studies for parameter estimation and control of discrete time systems are carried out by considering a numerical example of flight control problem.