predict(idnlhw) - Predict output k steps ahead for Hammerstein-Wiener model

Syntax

YP = predict(MODEL,DATA,K) YP = predict(MODEL,DATA,K,INIT) YP = predict(MODEL,DATA,K,'InitialState',INIT)

YP = predict(MODEL,DATA,K) predicts the k-step ahead output with an idnlhw model.

YP = predict(MODEL,DATA,K,INIT) or YP = predict(MODEL,DATA,K,'InitialState',INIT) specifies the initialization.

MODEL: idnlhw model object.
DATA: iddata object.
K: Prediction horizon. Old outputs up to time t-K are used to predict the output at time t. All relevant inputs are used. Default value: K = 1).
INIT: Initialization specification. INIT can be the following:
- 'e': Estimate initial states minimizing the sum of squared prediction errors. To compute the initial state estimates explicitly, use findstates(idnlhw).
- Real column vector X0 for the initial state vector. To build an initial state vector from a given set of input-output data or to generate equilibrium states, see findstates(idnlhw) and findop(idnlhw). For multi-experiment data, X0 may be a matrix whose columns give different initial states for different experiments.
- 'z': (Default) Zero initial state, equivalent to a zero vector of appropriate size.

YP: Predicted output as an iddata object. If DATA contains multiple experiments, so will YP.

Note If predict is called without an output argument, MATLAB software displays the predicted output(s) in a plot window.