wA2 - 11:20 Optimal finite-sample experiment design in worst-case system identification

In this paper we investigate finite sample optimality properties for the worst case el identification of the impulse response of discrete time, linear, time invariant systems. The experimental conditions we consider consist of one or more finite input-output sequences. The measured outputs are corrupted by additive disturbances, known only to be component-wise bounded. Optimality of the experimental data is measured by the diameter of information. It is shown that if the system has finite memory n + 1 and at most n + 1 output values are measured, then the number of experiments that define optimal information must be exponential in n. We also show that, in the case of one input and no a priori information, the impulsive input is optimal.