The model estimation methods in Cha

The model estimation methods in Chapter 3, Nonparametric ModelEstimation Methods, Chapter 4, Parametric Model Estimation Methods,Chapter 5, Partially Known Model Estimation Methods, and Chapter 6,Model Estimation Methods in Closed-Loop Systems, use nonrecursivemethods to estimate a model of the plant in a system. Nonrecursive modelestimation identifies a model for a plant based on input-output datagathered at a time prior to the current time. However, many real-worldapplications such as adaptive control and adaptive prediction, having amodel of the system update while the system is running is necessary orhelpful. In this type of application, you obtain the mathematical model ofthe system in real time.Recursive model estimation is a common system identification techniquethat enables you to develop a model that adjusts based on real-time datacoming from the system. Recursive model estimation processes themeasured input-output data recursively as the data becomes available. Thischapter discusses recursive model estimation techniques and variousadaptive algorithms associated with each method.