Design of adaptive feedforward controllers using internal model equivalence

Abstract

The paper investigates the design of adaptive feedforward cancellation (AFC) algorithms with sinusoidal regressors for repetitive control. Such adaptive algorithms are equivalent to a linear controllers based on the internal model principle. Using this equivalence and root locus rules, the phase advance of the regressor of the adaptive algorithm can be chosen to maximize the phase margin at low gains. It is shown that selecting the optimal phase advance is equivalent to placing a zero in the open right half-plane in certain cases. Complete design and analysis for the compensation of a single frequency periodic disturbances is done. A new variation of the AFC algorithm is also developed in which the adaptive portion acts in parallel with a feedthrough term. The IMP equivalent of this algorithm has two zeros instead of one. Analysis and simulation shows this method to have superior convergence and robustness properties when compared with the method having no feedthrough term.