Adaptive optimal robust stabilization of autoregressive plant under biased external disturbance

This paper addresses the problem of adaptive optimal robust 
control of a discrete-time plant with unknown parameters 
of autoregressive nominal model, unknown upper bound and 
bias of external disturbance, and unknown gains of coprime 
factor perturbations. The control criterion is the worst-case 
steady-state upper bound of the output. Solution of the problem 
is based on an optimal polyhedral estimation of unknown 
non-identifiable parameters with the control criterion treated 
as the identification criterion. A replacement of unknown parameters 
is proposed that modifies the plant model to a model 
without perturbation in control. This transforms the nonconvex 
control criterion to a linear fractional one and thus makes 
possible online computation of optimal estimates.