Model reference robust control

Abstract

Classical model reference adaptive control schemes require the following assumptions on the plant: A1) minimum phase; A2) known upper bound of the plant order; A3) known relative degree; and A4) known sign of high frequency gain. It is well-known that the robustness of the adaptive systems is a potential problem, and it requires many sophisticated techniques to fix it. In this paper, we consider the same model reference control problem via robust control. By further assuming that the boundedness of the parameter uncertainties of the plant (which is a very weak assumption), we show that a linear time-invariant dynamic output feedback controller can be constructed to give the following property: the closed-loop system is internally stable and its transfer function is arbitrarily close to the reference model. This method provides simple controllers and good robustness. It also has potential to cope with large size fast time-varying uncertainties.

This work is supported by the Australian Research Council.