Time Series Recursions and Self-Tuning Control

Recursive estimates are estimates (of parameters in a time series model) that are computed in a sequential fashion (i.e. updated quickly as new observations become available). The uses of such “real” time parameter estimators include real-time forecasting and self-tuning control. Here it is shown how “real” time parameter estimators can be constructed for time series models; also an heuristic discussion of their convergence behavior is given. The analysis and synthesis of self-tuning controllers is also discussed.