Simulate Hammerstein-Wiener model in Simulink software
System Identification Toolbox / Models
The Hammerstein-Wiener Model block simulates the output of a
Hammerstein-Wiener model using time-domain input data. The model is an
idnlhw model that you previously estimated or constructed in the
MATLAB® workspace. You specify initial conditions for the simulation as one of the
Zero for all states
Initial state vector representing the initial states of the linear block
For information about the structure of a Hammerstein-Wiener model, see What are Hammerstein-Wiener Models?.
Port_1(In1) — Simulation input data
scalar | vector
Simulation input data, specified as a scalar for a single-input model. The data must be time-domain data. For multi-input models, specify the input as an Nu-element vector, where Nu is the number of inputs. For example, you can use a Vector Concatenate (Simulink) block to concatenate scalar signals into a vector signal.
Port_1(Out1) — Simulated output
scalar | vector
Simulated output from Hammerstein-Wiener model, returned as a scalar for a single-output model and as an Ny-element vector for a model with Ny outputs.
Initial conditions — Initial condition specification for simulation
Zero (default) |
The states of a Hammerstein-Wiener model correspond to the states of the
model. For more information about the states, see the
idnlhw reference page. You
Initial conditions as one of the
Zero— Specifies zero initial state values, which correspond to a simulation starting from a state of rest.
State values— You specify the state values in Specify a vector of state values. Specify the states as a vector of length equal to the number of states in the model.
If you do not know the initial states, you can estimate these states as follows:
To simulate the model around a given input level when you do not know the corresponding output level, you can estimate the equilibrium state values using the
For example, to simulate a model
Mabout a steady-state point where the input is
1and the output is unknown, you can specify the initial state values as
X0 = findop(M,'steady',1,NaN)
To estimate the initial states that provide a best fit between measured data and the simulated response of the model for the same input, use the
For example, to compute initial states such that the response of the model
Mmatches the simulated output data in the data set
X0, such that:
X0 = findstates(M,z)