Quasi-Deadbeat Minimax Estimation for Deterministic Generic Linear Models

In this paper, a quasi-deadbeat minimax estimation (QME) is proposed as a new class of time-domain parameter estimations for deterministic generic linear models. Linearity, quasi-deadbeat property, FIR structure, and independency of the initial parameter information will be required in advance, in addition to a new performance criterion of a worst case gain between the disturbances and the current estimation error. The proposed QME is obtained in a closed form by directly solving an optimization problem. The QME is represented in both a batch form and an iterative form. A fast algorithm for the suggested estimation is also presented, which is remarkable in view...