Robust performance of adaptive controllers with general uncertainty structure

Sufficient conditions are given under which an adaptive control system is robustly stable and achieves a guaranteed robust asymptotic performance level equal to that of the robust controller given perfect parameter information. The conditions are general in several respects. For example, structured nonparametric uncertainty (e.g., block diagonal) is allowed as well as exogenous noise inputs. In addition, the structure of the parametric uncertainty is very general and allows for parameters which scale the uncertainty magnitudes. This allows one to identify the size of the nonparametric uncertainty and to schedule the controller based on this size. The robust gain scheduled controller is largely unrestricted. For this general problem, concrete robust identification mechanisms have not yet been found