Adaptive learning control of linear systems by output error feedback
Abstract
This paper addresses the problem of designing an output error feedback tracking control for single-input, single-output, minimum phase, observable linear systems. The reference output signal is assumed to be smooth and periodic with known period. By developing in Fourier series expansion a suitable periodic input reference signal, an output error feedback adaptive learning control is designed which 'learns' the input reference signal by identifying its Fourier coefficients: exponential tracking of both the input and the output reference signals is achieved if the Fourier series expansion is finite while arbitrary small tracking errors are guaranteed otherwise.