ROBUST ADAPTIVE REGULATION WITH MINIMAL PRIOR KNOWLEDGE

In this paper, a new robust adaptive regulator is designed under minimal prior knowledge, namely the order of a nominal plant model (in a well defined sense). The involved robustness means that the closed-loop stability is guaranteed in the presence of some class of time-varying parameters and unmodeled dynamics. The main design feature of the proposed adaptive regulator consists in its self-excitation capability together with an appropriate identification-stabilization time splitting. Unlike in the available literature concerning robust adaptive control, the involved self-excitation is established independently of the parameter estimator properties. The use of those robustness oriented modification as deadzone and parameter projection or contraction, which are aimed at achieving the parameter estimates boundedness, are no longer a priori required, reducing henceforth the underlying prior knowledge.