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sys = iv4(data,[na
nb nk])
sys = iv4(data,'na',na,'nb',nb,'nk',nk)
sys = iv4(data,[na
nb nk],Name,Value)
sys = iv4(data,[na
nb nk],___,opt)
sys = iv4(data,[na nb nk]) estimates an ARX polynomial model, sys, using the four-stage instrumental variable method, for the data object data. [na nb nk] specifies the ARX structure orders of the A and B polynomials and the input to output delay. The estimation algorithm is insensitive to the color of the noise term.
sys is an ARX model:
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Alternatively, you may also use the following syntax:
sys = iv4(data,'na',na,'nb',nb,'nk',nk)
sys = iv4(data,[na nb nk],Name,Value) estimates an ARX polynomial with additional options specified by one or more Name,Value pair arguments.
sys = iv4(data,[na nb nk],___,opt) uses the option set, opt, to configure the estimation behavior.
data |
Estimation time series data. data must be an iddata object. |
[na nb nk] |
ARX polynomial orders. For multi-output model, [na nb nk] contains one row for every output. In particular, specify na as an Ny-by-Ny matrix, where each entry is the polynomial order relating the corresponding output pair. Here, Ny is the number of outputs. Specify nb and nk as Ny-by-Nu matrices, where Nu is the number of inputs. For more details on the ARX model structure, see arx. |
opt |
Estimation options. opt is an options set that configures the estimation options. These options include:
Use iv4Options to create the options set. |
Specify optional comma-separated pairs of Name,Value arguments, where Name is the argument name and Value is the corresponding value. Name must appear inside single quotes (' '). You can specify several name and value pair arguments in any order as Name1,Value1,...,NameN,ValueN.
sys |
Identified polynomial model of ARX structure. sys is an idpoly model which encapsulates the identified polynomial model. |
Estimate a two-input, one-output system with different delays on the inputs u1 and u2.
z = iddata(y, [u1 u2]); nb = [2 2]; nk = [0 2]; m= iv4(z,[2 nb nk]);
Estimation is performed in 4 stages. The first stage uses the arx function. The resulting model generates the instruments for a second-stage IV estimate. The residuals obtained from this model are modeled as a high-order AR model. At the fourth stage, the input-output data is filtered through this AR model and then subjected to the IV function with the same instrument filters as in the second stage.
For the multiple-output case, optimal instruments are obtained only if the noise sources at the different outputs have the same color. The estimates obtained with the routine are reasonably accurate, however, even in other cases.
[1] Ljung, L. System Identification: Theory for the User, equations (15.21) through (15.26), Upper Saddle River, NJ, Prentice-Hal PTR, 1999.
armax | arx | bj | idpoly | iv4Options | ivx | n4sid | oe | polyest

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