Neural State-Space Model

Libraries:
      System Identification Toolbox / 
      Models
   
Description
Simulates neural state-space (idNeuralStateSpace) models.
Ports
Input
Input of the neural state-space model, specified as a vector signal with as many
              elements as the number of inputs you specify when creating the corresponding
                idNeuralStateSpace object. If the
                idNeuralStateSpace object specified in the block dialog box does
              not have inputs, this port does not appear.
Initial state of the neural state-space model, specified as a vector signal with
              as many elements as the number of states you specify when creating the corresponding
                idNeuralStateSpace object.
Dependencies
To enable this input port, select the initial state source
                parameter as External. Then, connect the port to an
                upstream signal supplying the value of the initial state.
Output
Output of the neural state-space model, returned as a vector signal with as many
              elements as the number of outputs you specify when creating the corresponding
                idNeuralStateSpace object.
State of the neural state-space model, output as a vector signal with as many
              elements as the number of states nx that you
              specify when creating the corresponding idNeuralStateSpace object.
              These values are identical to the first nx
              values in the y output.
Dependencies
To enable this output port, select the Output state parameter.
State derivative or state difference of the neural state-space model, output as a
              vector signal with as many elements as the number of states you specify when creating
              the corresponding idNeuralStateSpace object. 
For continuous-time neural state space models, this value is the derivative of the state with respect to time. For discrete-time neural state space models, this value is the difference between the next state and the current one.
Dependencies
To enable this output port, select the Output state derivative/difference parameter.
Internal (latent) state of the neural state-space model, output as a vector signal
              with as many elements as the value of the LatentDim
              property that you specify when creating the corresponding
                idNeuralStateSpace object. 
Dependencies
To enable this output port, specify the value of the
                  LatentDim property of the idNeuralStateSpace
                object as a finite positive scalar and select the Output state
                parameter.
Internal (latent) state derivative or latent state difference of the neural
              state-space model, output as a vector signal with as many elements as the value of the
                LatentDim
              property that you specify when creating the corresponding
                idNeuralStateSpace object. 
For continuous-time neural state space models, this value is the derivative of the latent state with respect to time. For discrete-time neural state space models, this value is the difference between the next latent state and the current one.
Dependencies
To enable this output port, specify the value of the
                  LatentDim property of the idNeuralStateSpace
                object as a finite positive scalar and select the Output state
                  derivative/difference parameter.
Parameters
Specify an idNeuralStateSpace object that defines a neural state-space system by
            entering the name of an idNeuralStateSpace object from the
              MATLAB® workspace.
Currently, the Neural State-Space Model block does not support
              idNeuralStateSpace objects whose neural network layer activation
            functions are elu, swish,
              softplus, or scaling.
Note
If you change the input/output configuration of Model in the
              workspace, click the ... button next to the
                Model edit field in the block dialog box to refresh the
                Neural State-Space Model block.
Programmatic Use
| Block Parameter: sys | 
| Type: string, character vector | 
| Default: "idNeuralStateSpace(1,'NumInputs',1,'NumOutputs',2)" | 
Specify whether to enter the initial condition directly on the dialog box or to receive the initial condition from an input port.
- If you set Initial state source to - internal, enter the initial condition in the edit field under Initial state.
- If you set Initial state source to - external, the input port- x0is added to the block. You must then connect an upstream signal supplying the value of the initial state to the- x0input port.
Programmatic Use
| Block Parameter: x0type | 
| Type: character vector | 
| Values: 'internal'|'external' | 
| Default: 'internal' | 
Specify the initial state of the neural state-space object as a vector of
                nx entries, where
                nx is the number of states in
              Model.
Use this parameter make sure that the system states reflect the true plant environment at the start of your simulation, to the best of your knowledge.
Programmatic Use
| Block Parameter: ic | 
| Type: string, character vector | 
| Default: "0" | 
Select this parameter to add the x output port to the block.
            During simulation this port outputs the internal state of the idNeuralStateSpace object specified in Model.
Programmatic Use
| Block Parameter: returnx | 
| Type: string, character vector | 
| Values: "off","on" | 
| Default: "off" | 
Select this parameter to add the dx output port to the block.
            During simulation this port outputs the time derivative of the internal state of the
              idNeuralStateSpace object specified in Model.
Programmatic Use
| Block Parameter: returndx | 
| Type: string, character vector | 
| Values: "off","on" | 
| Default: "off" | 
Extended Capabilities
C/C++ Code Generation
 Generate C and C++ code using Simulink® Coder™.
Version History
Introduced in R2022bStarting in 2024b, temporary .m files will no longer be created in
        the current folder when updating the Neural State-Space Model Block for
        prediction and code generation. 
However, if the structure of the dlnetwork object assigned to the state
        or output networks of the neural state-space object is not a multi-layer perceptron (MLP)
        network, then the implementation of the Neural State-Space Model Block uses
        the Predict (Deep Learning Toolbox) Block and
          .mat files will still be generated in the current folder. In all other
        cases, .mat files will also not be created.
See Also
Objects
Functions
- nlssest|- createMLPNetwork|- setNetwork|- nssTrainingOptions|- generateMATLABFunction|- sim|- idNeuralStateSpace/evaluate|- idNeuralStateSpace/linearize
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