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simsdOptions

Option set for simsd

Syntax

opt = simsdOptions
opt = simsdOptions(Name,Value)

Description

example

opt = simsdOptions creates the default option set for simsd.

example

opt = simsdOptions(Name,Value) creates an option set with the options specified by one or more Name,Value pair arguments.

Examples

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opt = simsdOptions;

Create an option set for simsd specifying the following options.

  • Zero initial conditions

  • Input offset of 5 for the second input of a two-input model

opt = simsdOptions('InitialCondition','z','InputOffset',[0; 5]);

Create a default option set.

opt = simsdOptions;

Modify the option set to add noise to the data.

opt.AddNoise = true;

When you use this option set and simsd command to simulate the response of a model sys. The command returns the perturbed realizations of sys with additive disturbances added to each response.

Input Arguments

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Name-Value Pair Arguments

Specify optional comma-separated pairs of Name,Value arguments. 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.

Example: opt = simsdOptions('AddNoise',true','InputOffset',[5;0]) adds default Gaussian white noise to the response model, and specifies an input offset of 5 for the first of two model inputs.

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Simulation initial conditions, specified as one of the following:

  • 'z' — Zero initial conditions.

  • Numerical column vector X0 of initial states with length equal to the model order.

    For multi-experiment data, specify a matrix with Ne columns, where Ne is the number of experiments, to configure the initial conditions separately for each experiment. Otherwise, use a column vector to specify the same initial conditions for all experiments.

    Use this option for state-space models (idss and idgrey) only. You can also specify the covariance of the initial state vector in X0Covariance.

  • Structure with the following fields, which contain the historical input and output values for a time interval immediately before the start time of the data used in the simulation:

    FieldDescription
    InputInput history, specified as a matrix with Nu columns, where Nu is the number of input channels. For time-series models, use []. The number of rows must be greater than or equal to the model order.
    OutputOutput history, specified as a matrix with Ny columns, where Ny is the number of output channels. The number of rows must be greater than or equal to the model order.

    For multi-experiment data, you can configure the initial conditions separately for each experiment by specifying InitialCondition as a structure array with Ne elements. Otherwise, use a single structure to specify the same initial conditions for all experiments.

    The software uses data2state to map the historical data to states. If your model is not idss or idgrey, the software first converts the model to its state-space representation and then maps the data to states. If conversion of your model to idss is not possible, the estimated states are returned empty.

Covariance of initial states vector, specified as one of the following:

  • Positive definite matrix of size Nx-by-Nx, where Nx is the model order.

    For multi-experiment data, specify as an Nx-by-Nx-by-Ne matrix, where Ne is the number of experiments. For the kth experiment, X0Covariance(:,:,k) specifies the covariance of initial states X0(:,k).

  • [] — No uncertainty in the initial states.

Use this option for state-space models (idss and idgrey) when 'InitialCondition' is specified as a numerical column vector X0. When you specify this option, the software uses a different realization of the initial states to simulate each perturbed model. Initial states are drawn from a Gaussian distribution with mean InitialCondition and covariance X0Covariance.

Input signal offset, specified as a column vector of length Nu. Use [] if there are no input offsets. Each element of InputOffset is subtracted from the corresponding input data before the input is used to simulate the model.

For multiexperiment data, specify InputOffset as:

  • An Nu-by-Ne matrix to set offsets separately for each experiment.

  • A column vector of length Nu to apply the same offset for all experiments.

Output signal offset, specified as a column vector of length Ny. Use [] if there are no output offsets. Each element of OutputOffset is added to the corresponding simulated output response of the model.

For multiexperiment data, specify OutputOffset as:

  • An Ny-by-Ne matrix to set offsets separately for each experiment.

  • A column vector of length Ny to apply the same offset for all experiments.

Noise addition toggle, specified as a logical value indicating whether to add noise to the response model. Set NoiseModel to true to study the effect of additive disturbances on the response. A different realization of the noise sequence, consistent with the noise component of the perturbed system, is added to the noise-free response of that system.

Output Arguments

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Option set for simsd command, returned as a simsdOptions option set.

See Also

Introduced in R2012a

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