A stable adaptive implementation of the internal model principle

An adaptive implementation of the internal model principle for linear time-invariant systems that allows for rejection of unknown deterministically modeled disturbances is provided. The minimal representation of the system model is used for parameter estimation, and the global convergence and stability of the algorithm are investigated with unmodeled dynamics. With proper modification of the parameter estimation algorithm, global convergence and stability for the algorithm are obtained without the requirement of persistent excitation. Some simulation results are given to support the analysis