Recursive functional series modeling estimators for identification of time-varying plants-more bad news than good?

The properties of a class of recursive estimators-the exponentially weighted functional series modeling estimators-are discussed. These estimators can be used, e.g. in adaptive prediction or control applications. It is argued that there exists a relationship between the amount of information about time-varying system parameters, which is available a priori, and the robustness of the identification algorithm based on such prior knowledge. The more specialized the estimation algorithm is, the less reliable it might be under nonstandard conditions. This is the reason why simple algorithms such as exponentially weighted least squares have to be recommended as if no information about the system nonstationarity is available in advance. >