Abstract
This paper addresses the problem of adaptive optimal robust
 tracking for a discrete-time plant with unknown parameters
 of autoregressive nominal model and unknown bias of
 bounded external disturbance. Upper bounds of unbiased external
 disturbance and gains of uncertainties in output and
 control are assumed to be know. The optimal tracking problem
 is to minimize the guaranteed worst-case steady-state
 upper bound of the tracking error for a given bounded reference
 signal. Solution of the problem is based on optimal
 set-membership estimation of unknown non-identifiable parameters
 and treating the control criterion as the identification
 criterion. Optimal on-line set-membership estimation
 becomes computationally tractable due to a linear-fractional
 representation of the control criterion.
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