A discrete-time learning control algorithm for a class of linear time-invariant systems

Abstract

A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. A necessary and sufficient condition for uniform convergence of the proposed learning algorithm is presented. Then, we prove that the same condition is sufficient for the global robustness of the proposed learning algorithm to state disturbances, measurement noise at the output, and reinitialization error are present at each iteration. A numerical example is given to illustrate the results.