州空间模型are models that use state variables to describe a system by a set of first-order differential or difference equations, rather than by one or morenth阶差分或差方程。状态变量X((t)can be reconstructed from the measured input-output data, but are not themselves measured during an experiment.
状态空间模型结构是快速估计的一个不错的选择,因为它要求您仅指定一个输入,即模型顺序,,,,n。模型顺序是一个等于尺寸的整数X((t)并与相应的线性差方程中使用的延迟输入和输出的数量有关,但不一定等于。
It is often easier to define a parameterized state-space model in continuous time because physical laws are most often described in terms of differential equations. In continuous-time, the state-space description has the following form:
矩阵F,,,,G,,,,H,,,,anddcontain elements with physical significance—for example, material constants.X0指定初始状态。
您可以使用时域和频域数据估算连续的状态空间模型。
the discrete-time state-space model structure is often written in the创新形式描述噪音:
在哪里tis the sample time,你((kt)is the input at time instantkt,,,,andy((kt)is the output at time instantkt。
您无法使用连续时间频域数据估算离散的状态空间模型。
For more information, see什么是州空间模型?
System Identification | 从测量数据中识别动态系统的模型 |
Estimate State-Space Model | Estimate state-space model using time or frequency data in the Live Editor |
州空间模型are models that use state variables to describe a system by a set of first-order differential or difference equations, rather than by one or morenth阶差分或差方程。
State-Space Model Estimation Methods
在非词法子空间方法之间进行选择,使用预测误差最小化算法的迭代方法和非读写方法。
to estimate a state-space model, you must provide a value of its order, which represents the number of states.
Canonical State-Space Realizations
Modal, companion, observable and controllable canonical state-space models.
您可以使用真实或复杂且具有单个或多个输出的时间域和频域数据。
将数据导入系统标识应用程序。
执行黑框或结构化估计。
规范参数化represents a state-space system in a reduced parameter form where many elements of一个,,,,bandCmatrices are fixed to zeros and ones.
此示例显示了如何使用状态空间估计方法估算ARMAX和OE形式模型。
Estimate State-Space Models with Free-Parameterization
状态空间矩阵的默认参数化一个,,,,b,,,,C,,,,d,,,,andk免费;也就是说,矩阵中的任何元素均可通过估计例程调节。
Use State-Space Estimation to Reduce Model Order
减少模拟的顺序万博1manbetx®model by linearizing the model and estimating a lower-order model that retains model dynamics.
Structured parameterizationlets you exclude specific parameters from estimation by setting these parameters to specific values.
Identifying State-Space Models with Separate Process and Measurement Noise Descriptions
确定的线性模型用于模拟和预测给定输入和噪声信号的系统输出。
Supported State-Space Parameterizations
系统标识Toolbox™软件支持以下参数化,该参数表明估计了哪些参数,哪些参数仍万博1manbetx以特定值固定:
When you estimate state-space models, you can specify how the algorithm treats initial states.