A Stable Adaptive Implementation of the Internal Model Principle

This note provides a new adaptive implementation of the internal model principle for linear time-invariant systems, which allows for rejection of unknown deterministically modeled disturbances. 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, this note presents global convergence and stability for the new algorithm without the requirement of persistent excitation. Some simulation results are given to support our analysis. © 1992 IEEE