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 nonlinear systems with unknown smooth output dependent nonlinearities. 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 output reference signals is achieved if the Fourier series expansion is finite while arbitrary small tracking errors are exponentially guaranteed otherwise.

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