MATLAB SYSTEM IDENTIFICATION TOOLBOX 7 Betriebsanweisung PDF herunterladen (Seite 139)

100

101

Generating Data Using Simulation

% Construct input data and noise

u = iddata([],u,'Period',10);

e = iddata([],randn(1500,1));

% Simulate model output with noise

y = sim(m0,[u e])

% Estimate frequency response

g = etfe([y u])

% Generate Bode plot

bode(g,'x',m0)

For periodic input, etfe honors the p eriod a nd computes the frequency

response using an appropriate frequency grid. In this case, the Bode plot

shows a good ﬁtattheﬁve excited f requencies.

Example – Generating Data Using Simulation

This example dem onstrates how you can create input data and a model, and

then use the data and the model to simulate output data. You create the

ARMAX model and simulate output data with random binary input

1 Load the three-input and one-output sample data.

load iddata8

2 Construct an ARM AX model, using the following commands:

A = [1 -1. 2 0.7];

B(1,:) = [0 1 0.5 0.1]; % first input

B(2,:) = [0 1.5 -0.5 0]; % second input

B(3,:) = [0 -0.1 0.5 -0.1]; % third input

C=[10000];

Ts = 1;

m = idpoly(A,B,C,'Ts',1);

In this example, the leading zeros in the B matrix indicate the input delay

(

nk), which is 1 for each input channel. The trailing zero in B(2,:) makes

the number of coefﬁcients equal for all channels.

3 Construct pseudorandom binary data for input to the simulation.

u = idinput([200,3],'prbs');

1-117

1 2 ... 134 135 136 137 138 139 140 141 142 143 144 ... 530 531

Kommentare zu diesen Handbüchern

Keine Kommentare

MATLAB SYSTEM IDENTIFICATION TOOLBOX 7 Betriebsanweisung Seite 139

Kommentare zu diesen Handbüchern

Verwandte Produkte und Handbücher für Software MATLAB SYSTEM IDENTIFICATION TOOLBOX 7