Advances on adaptive learning control: The case of non-minimum phase linear systems

Abstract

The adaptive learning control theory is extended to include the case of non-minimum phase (time-invariant) linear systems with uncertain parameters. The existence of two approximate solutions to the related output tracking problem is proved. Exponential tracking of periodic output reference signals is guaranteed, along with the exponential estimation of the constant system parameters and of the constant coefficients characterizing the truncated Fourier series expansion for the periodic input reference signal.