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Sparse Second Order

Represent sparse second-order models in Simulink

Since R2020b

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  • Sparse Second Order block

Libraries:
Control System Toolbox

Description

The Sparse Second Order block lets you represent second-order sparse state-space models, in Simulink®. Such sparse models arise from finite element analysis (FEA) and are useful in fields like structural analysis, fluid flow, heat transfer and electromagnetics. The resultant matrices from this type of modeling are quite large with a sparse pattern. In continuous time, a second-order sparse mass-spring-damper state-space model is represented in the following form:

M q¨(t)+C q˙(t)+K q(t) = B u(t)y(t) = F q(t)+G q˙(t)+D u(t)

Here, the full state vector is given by [q,q˙], where q and q˙ are the displacement and velocity vectors. u and y represent the inputs and outputs, respectively. M, C, and K represent the mass, damping and stiffness matrices, respectively. B is the input matrix, while F and G are the output matrices resulting from the two components of the state vector. D is the input-to-output matrix.

Examples

Linearize Simulink Model to a Sparse Second-Order Model Object

Linearize Simulink Model to a Sparse Second-Order Model Object

Linearize to a sparse second-order model object from your Simulink model using Simulink Control Design™ software.

Ports

Input

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Real-valued input vector of type double whose size is equal the number of columns in the B and D matrices.

Data Types: double

Output

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Real-valued output vector of type double whose size is equal to the number of rows in the F, G and D matrices.

Data Types: double

Parameters

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Mass matrix, specified as an Nq-by-Nq sparse matrix where, Nq is the number of nodes.

Programmatic Use

Block Parameter: M
Type: scalar, square sparse matrix
Default: 1

Damping matrix, specified as an Nq-by-Nq sparse matrix where, Nq is the number of nodes.

Programmatic Use

Block Parameter: C
Type: scalar, square sparse matrix
Default: 0

Stiffness matrix, specified as an Nq-by-Nq sparse matrix where, Nq is the number of nodes.

Programmatic Use

Block Parameter: K
Type: scalar, square sparse matrix
Default: 1

Input-to-state matrix, specified as an Nq-by-Nu sparse matrix where, Nq is the number of nodes and Nu is the number of inputs.

Programmatic Use

Block Parameter: B
Type: scalar, sparse matrix
Default: 1

Displacement-to-output matrix, specified as an Ny-by-Nq sparse matrix where, Nq is the number of nodes and Ny is the number of outputs.

Programmatic Use

Block Parameter: F
Type: scalar, sparse matrix
Default: 1

Velocity-to-output matrix, specified as an Ny-by-Nq sparse matrix where, Nq is the number of nodes and Ny is the number of outputs.

Programmatic Use

Block Parameter: G
Type: scalar, sparse matrix
Default: 0

Input-to-output matrix, specified as an Ny-by-Nu sparse matrix where, Ny is the number of outputs and Nu is the number of inputs.

Programmatic Use

Block Parameter: D
Type: scalar, sparse matrix
Default: 0

Initial values for displacement vector q, specified as a vector of doubles. q and q˙ are the displacement and velocity vectors that make up the state vector.

Programmatic Use

Block Parameter: q0
Type: scalar, vector of doubles
Default: 0

Initial values for velocity vector q˙, specified as a vector of doubles. q and q˙ are the displacement and velocity vectors that make up the state vector.

Programmatic Use

Block Parameter: dq0
Type: scalar, vector of doubles
Default: 0

Note

For linearization with Simulink Control Design, the linearized model is a mechss model object when the Sparse Second Order block is present in your Simulink model.

For more information, see Sparse Model Basics.

For an example, see Linearize Simulink Model to a Sparse Second-Order Model Object.

Extended Capabilities

Version History

Introduced in R2020b

See Also

Topics