Pole assignment and tracking of uncertain linear systems with state/output feedback: a model reference adaptive control approach

This paper presents an adaptive feedback and feedforward control scheme for uncertain linear systems which drives the response of uncertain system to the desired one. By using the simple adaptive rules for feedback gain and feedforward input, it is shown that all the error signals are bounded and the tracking error converges to zero asymptotically. A persistent exciting signals in the domain of discrete time is defined and used in proving convergence of the adaptive feedback gain and feedforward learning input to their true values. The effectiveness of proposed control scheme is demonstrated via computer simulation.