getDelayInfo

Get input/output delay information for idnlarx model structure

Syntax

DELAYS = getDelayInfo(MODEL) DELAYS = getDelayInfo(MODEL,TYPE)

Description

DELAYS = getDelayInfo(MODEL) obtains the maximum delay in each input and output variable of an idnlarx model.

DELAYS = getDelayInfo(MODEL,TYPE) lets you choose between obtaining maximum delays across all input and output variables or maximum delays for each output variable individually. When delays are obtained for each output variable individually a matrix is returned, where each row is a vector containing n_y+n_u maximum delays for each output variable, and:

n_y is the number of outputs of MODEL.
n_u is the number of inputs of MODEL.

Delay information is useful for determining the number of states in the model. For nonlinear ARX models, the states are related to the set of delayed input and output variables that define the model structure (regressors). For example, if an input or output variable p has a maximum delay of D samples, then it contributes D elements to the state vector:

p(t-1), p(t-2), ...p(t-D)

The number of states of a nonlinear ARX model equals the sum of the maximum delays of each input and output variable. For more information about the definition of states for idnlarx models, see Definition of idnlarx States

Input Arguments

getDelayInfo accepts the following arguments:

MODEL: idnlarx model.
TYPE: (Optional) Specifies whether to obtain channel delays 'channelwise' or 'all' as follows:
- 'all': Default value. DELAYS contains the maximum delays across each output (vector of n_y+n_u entries, where [ny, nu] = size(MODEL)).
- 'channelwise': DELAYS contains delay values separated for each output (n_y-by-(n_y+n_u) matrix).

Output Arguments

DELAYS: Contains delay information in a vector of length n_y+n_u arranged with output channels preceding the input channels, i.e., [y1, y2,.., u1, u2,..].

Examples

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Get Input and Output Delay Information for Nonlinear ARX Model

Open Live Script

Create a two-output, three-input nonlinear ARX model.

M = idnlarx([2 0 2 2 1 1 0 0; 1 0 1 5 0 1 1 0],'linear');

Compute the maximum delays for each output variable individually.

Del = getDelayInfo(M,'channelwise')

Del = 2×5

     2     0     2     1     0
     1     0     1     5     0

The matrix Del contains the maximum delays for the first and second output of model M. You can interpret the contents of matrix Del as follows:

In the dynamics for output 1 ( $y_{1}$ ), the maximum delays in channels $y_{1}$ , $y_{2}$ , $u_{1}$ , $u_{2}$ , $u_{3}$ are 2, 0, 2, 1, and 0 respectively.
Similarly, in the dynamics for output 2 ( $y_{2}$ ) of the model, the maximum delays in channels $y_{1}$ , $y_{2}$ , $u_{1}$ , $u_{2}$ , $u_{3}$ are 1, 0, 1, 5, and 0 respectively.

Find maximum delays for all the input and output variables in the order $y_{1}$ , $y_{2}$ , $u_{1}$ , $u_{2}$ , $u_{3}$ .

Del = getDelayInfo(M,'all')

Del = 1×5

     2     0     2     5     0

Note, The maximum delay across all output equations can be obtained by executing MaxDel = max(Del,[],1). Since input $u_{2}$ has 5 delays (the fourth entry in Del), there are 5 terms corresponding to $u_{2}$ in the state vector. Applying this definition to all I/O channels, the complete state vector for model M becomes:

$X (t) = [y_{1} (t - 1), y_{1} (t - 2), u_{1} (t - 1), u_{1} (t - 2), u_{2} (t - 1), u_{2} (t - 2), u_{2} (t - 3), u_{2} (t - 4), u_{2} (t - 5)]$

Documentation