Reliable online adaptation of models with variable time delays

A new technique is presented for online adaptation of model parameters and time delays. The general case of continuous-time nonlinear models is considered, and the time delays are estimated to a fraction of the sampling period. The technique has the advantage that it requires user specification of only one parameter that determines the covered range of variability in the model parameters and time delays, whereas conventional techniques require a different user-specified parameter value corresponding to each particular variability. Prior knowledge of negligible or very high variability of certain model parameters or time delays can readily be incorporated into the proposed strategy. Performance of the technique is demonstrated on simulation runs for a single-input single-output system, with two parameters and one time delay, and comparisons are made with a conventional limited-memory estimator