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Model Interconnection VIs

LabVIEW 2012 Control Design and Simulation Module Help

Edition Date: June 2012

Part Number: 371894G-01

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Owning Palette: Control Design VIs and Functions

Requires: Control Design and Simulation Module. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.

Use the Model Interconnection VIs to perform different types of linear system interconnections. You can build a large system model by connecting smaller system models together.

The Model Interconnection VIs do not support the Stochastic Systems VIs.

The VIs on this palette can return general LabVIEW error codes or specific control design error codes.

Palette ObjectDescription
CD Add ModelsAdds two linear models. You also can use this VI to add a single-input single-output (SISO) model or a constant Gain to each element of a multiple-input multiple-output (MIMO) model. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD AppendAppends one linear model to another. The inputs and outputs of the Appended Model are the collective inputs and outputs of Model 1 and Model 2. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Divide ModelsDivides a linear model by a constant gain. This operation is equivalent to multiplying the model by the inverse of the gain. Therefore, if this VI cannot calculate the inverse of gain, LabVIEW returns an error. You also can divide two models by one another. In this situation, both models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Gain inputs to determine the polymorphic instance to use or manually select the instance.
CD FeedbackConnects two linear models in feedback configuration. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance. You can specify which outputs this VI feeds back to which inputs of the system. If you do not wire a model to Model 2, this VI assumes a unit feedback by defining Model 2 as the unit gain matrix. The number of connections in Feedback Connections defines the size of the unit gain matrix.
CD Horizontal ConcatenationConcatenates two linear models such that the Model Out is an array that contains these models as columns. The number of inputs of Model Out equals the number of inputs to Model 1 plus the number of inputs to Model 2. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Inverse ModelInverts a linear time-invariant (LTI) model in transfer function, zero-pole-gain, or state-space form. The model must neither have delay nor be strictly proper. Wire data to the Model In input to determine the polymorphic instance to use or manually select the instance.
CD Multiply ModelsMultiplies two linear models by using matrix multiplication. You also can multiply a multiple-input multiple-output (MIMO) model by a single-input single-output (SISO) model or by a constant Gain. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance. If you multiply two models, the number of outputs of Model 1 must be equal to the number of inputs of Model 2. The models either must be continuous-time models or must have the same sampling time if they are discrete-time models.
CD ParallelConnects two linear models in parallel. The system models must either be continuous-time models or have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Sensitivity FunctionsCalculates the sensitivity transfer functions necessary to evaluate a closed-loop system. Wire data to the Plant Model (P) and Controller Model (C) inputs to determine the polymorphic instance to use or manually select the instance.
CD SeriesConnects two linear models in series. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Subtract ModelsSubtracts linear models. This VI subtracts Model 2 from Model 1. You also can subtract a single-input single-output (SISO) model or a constant gain from each element of a multiple-input multiple-output (MIMO) model and vice-versa. The models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Transpose ModelTransposes a linear model such that the ij-th element of Model In becomes the ji-th element of Model Out. Wire data to the Model In input to determine the polymorphic instance to use or manually select the instance.
CD Unit FeedbackConnects two linear models in a unit feedback configuration. You can specify which outputs this VI feeds back to which inputs of the system. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.
CD Vertical ConcatenationConcatenates two linear models such that the Model Out is an array that contains these models as rows. The number of outputs ofModel Out equals the number of outputs from Model 1 plus the number of outputs from Model 2. The system models either must be continuous-time models or must have the same sampling time if they are discrete-time models. Wire data to the Model 1 and Model 2 inputs to determine the polymorphic instance to use or manually select the instance.

 

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