A class of algorithms for identification in H/sub infinity /: continuous-time case

The problem of system identification in H/sub infinity / for the continuous-time case is investigated. It is shown that the class of systems with a lower bound on the relative stability, an upper bound on the steady-state gain, and an upper bound on the roll-off rate is admissible. This allows one to develop a class of robustly convergent nonlinear algorithms. The algorithms in this class have a two-stage structure and are characterized by the use of window functions. Explicit worst-case error bounds in H/sub infinity / norm between the identified model and the unknown system are given for a particular algorithm. An example is provided to illustrate the application of the results obtained.<
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