  In controlling systems with large operating envelopes, it is often necessary
to adjust the desired dynamics according to operating conditions. This paper
presents a robust adaptive control architecture for linear parameter-varying
(LPV) systems that allows for the desired dynamics to be systematically
scheduled, while being able to handle a broad class of uncertainties, both
matched and unmatched, which can depend on both time and states. The proposed
controller adopts an L1 adaptive control architecture for designing the
adaptive control law and peak-to-peak gain (PPG) minimization for designing the
robust control law to mitigate the effect of unmatched uncertainties.
Leveraging the PPG bound of an LPV system, we derive transient and steady-state
performance bounds in terms of the input and output signals of the actual
closed-loop system as compared to the same signals of a nominal system. The
efficacy of the proposed method is validated by extensive simulations using the
short-period dynamics of an F-16 aircraft operating in a large envelope.
