An H∞ approach to robust adaptive control

Robust adaptive control is investigated using the H_infin approach. An equivalent measure to the H_infin-norm is adopted to quantify the unmodeled dynamics associated with adaptive estimation of the nominal model based on time-domain measurement data. Such an equivalent description for modeling errors allows H_infin optimization to be successfully used in adaptive control to achieve robust stability and performance comparable to H_infin control. The proposed adaptive control consists of the total least-squares (TLS) algorithm for adaptive model estimation, and H_infin-loopshaping for adaptive controller design. Our results show that the proposed adaptive control system admits robust stability and performance asymptotically, provided that the estimated plant model converges.