稀疏状态空间模型

具有稀疏数据的大型状态空间模型

在 MATLAB^® 和 Simulink^® 中高效地表示、组合和分析具有稀疏数据的大型状态空间模型。使用稀疏表示是理想和高效的做法，因为大型模型的稠密模型表示不仅计算成本相当高，还可能导致执行时间非常长。有关详细信息，请参阅稀疏矩阵的计算优点。

借助可用的功能，您可以：

使用稀疏模型执行时域和频域响应分析
指定稀疏模型之间以及与其他 LTI 模型的基于信号的连接
指定稀疏模型组件之间的物理耦合
在连续时间和离散时间表示之间变换稀疏模型
当您的 Simulink 模型具有 Descriptor State-Space (Simulink) 或 Sparse Second Order 模块时，使用 linearize (Simulink Control Design) 函数将其线性化为稀疏模型
使用 linearize (Partial Differential Equation Toolbox) 函数将结构性或热 PDE 模型线性化为稀疏模型

有关稀疏模型和可用功能的更多详细信息，请参阅Sparse Model Basics。

函数

`sparss`	Sparse first-order state-space model
`mechss`	Sparse second-order state-space model
`getx0`	Map initial conditions from a `mechss` object to a `sparss` object
`full`	Convert sparse models to dense storage
`imp2exp`	Convert implicit linear relationship to explicit input-output relation
`inv`	Invert dynamic system models
`getDelayModel`	State-space representation of internal delays
`findop`	Compute operating condition from specifications (自 R2023b 起)
`fixInput`	Fix value of some inputs and delete them (自 R2024a 起)
`sminDAE`	Reduce algebraic states in sparse state-space models while preserving sparsity (自 R2024b 起)

`sparssdata`	Access first-order sparse state-space model data
`mechssdata`	Access second-order sparse state-space model data
`showStateInfo`	State vector map for sparse model
`spy`	Visualize sparsity pattern of a sparse model

`step`	动态系统的阶跃响应
`impulse`	动态系统的冲激响应图；冲激响应数据
`initial`	系统对状态空间模型的初始状态的响应
`lsim`	计算动态系统对任意输入的时间响应仿真数据
`bode`	动态系统的波特频率响应
`nyquist`	动态系统的奈奎斯特响应
`nichols`	动态系统的尼柯尔斯响应
`sigma`	动态系统的频率响应的奇异值
`passiveplot`	Compute or plot passivity index as function of frequency
`dcgain`	LTI 系统的低频 (DC) 增益
`evalfr`	计算特定频率下的系统响应
`freqresp`	Evaluate system response over a grid of frequencies

`interface`	Specify physical connections between components of `mechss` model
`xsort`	Sort states based on state partition
`feedback`	多个模型的反馈连接
`parallel`	两个模型的并行连接
`append`	Group models by appending their inputs and outputs
`connect`	Block diagram interconnections of dynamic systems
`lft`	两个模型的广义反馈互连（雷德黑弗星积）
`series`	两个模型的串行连接

`linearize`	Linear approximation of Simulink model or subsystem
`linearizeOptions`	Set linearization options
`linio`	为 Simulink 模型、Linear Analysis Plots 模块或 Model Verification 模块创建线性分析点

`linearize`	(To be removed) Linearize structural or thermal model (自 R2021b 起)
`linearizeInput`	(To be removed) Specify inputs to linearized model (自 R2021b 起)
`linearizeOutput`	(To be removed) Specify outputs of linearized model (自 R2021b 起)

Descriptor State-Space	模型线性隐式系统
Sparse Second Order	Represent sparse second-order models in Simulink

Sparse Model Basics
Sparse models represent state-space systems composed of large sparse matrices.
Rigid Assembly of Model Components
Specify rigid physical couplings in a structural model.
Thermal Modeling and Control Design for CPU Chip Cooling System

Create a CPU and heat sink thermal model, perform model order reduction, and design a controller for a cooling system.
- 步骤 1: Create Heat Sink Finite Element Model and Export Data for State-Space Simulation
- 步骤 2: Import Finite Element Model Data to Simulink
- 步骤 3: Create Low-Order LPV Model of CPU and Heat Sink Model
- 步骤 4: Tune PI Controller for Heat Sink Model

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

Construct transient beam model and perform linear analysis.

Linearize a tuning fork structural model using Partial Differential Equation Toolbox™ software and perform linear analysis.

Compute a low-order approximation of a sparse state-space model obtained from linearizing a structural beam model.