You can linearize a Simulink® model at the default operating point defined in the model. For more information, see Linearize Simulink Model at Model Operating Point. You can also specify an operating point found using an optimization-based search or at a simulation time.
To extract the linearized response of a portion of your model, you can define specific linearization input and output points. For more information, see Specify Portion of Model to Linearize. After linearization, you can analyze and validate your results in both the time domain and frequency domain.
|Model Linearizer||Linearize Simulink models|
|Control Design Onramp with Simulink||Self-paced, interactive tutorial included with Simulink Control Design license|
|Linear approximation of Simulink model or subsystem|
|Set linearization options|
|Obtain linear analysis points from Simulink model, Linear Analysis Plots block, or Model Verification block|
|Create linear analysis point for Simulink model, Linear Analysis Plots block, or Model Verification block|
|Save linear analysis points to Simulink model, Linear Analysis Plots block, or Model Verification block|
|Linearize model while removing contribution of specified blocks|
|Combine linearization results from specified blocks and model|
|Fast restart for linear analysis|
Obtain a linear approximation of a nonlinear system that is valid in a small region around an operating point.
Simulink Control Design™ software lets you perform linear analysis of nonlinear models using a user interface, functions, or blocks.
Simulink Control Design software linearizes models using a block-by-block approach. The software individually linearizes each block in a Simulink model and produces the linearization of the overall system by combining the individual block linearizations.
Linearize a model at the operating point specified in the model. The model operating point consists of the model initial state values and input signals.
You can linearize a block or subsystem in your Simulink model without defining separate analysis points for the block inputs and outputs. The specified block or subsystem is isolated from the rest of the model before linearization.
You can analyze and compute the combined response of the plant and controller, excluding the effects of the feedback loop.
You can control the order of the states in a linearized model. This state order appears in linearization results.
You can linearize a Simulink model at an operating point that meets specified input, output, or state constraints.
Simulate a Simulink model and extract the state and input levels of the system at specified simulation times.
You can linearize a Simulink model at specific events in time. Linearization events can be trigger-based events or function-call events.
Specify the subsystem, loop, or block to linearize using linear analysis points.
Loop openings affect only how the software recombines linearized blocks, not how the software linearizes each block. The software ignores openings when computing operating points.
When linearizing a Simulink model with continuous-time delay blocks, you can either approximate the delays or represent the delays exactly.
You can linearize a Simulink model that contains blocks with different sample times.
To achieve an accurate block-by-block linearization of a model reference subsystem, first set it to run its simulation in normal mode.
You can linearize models with Simscape™ components using Simulink Control Design software.
Obtain sparse linear systems from Simulink models that contain Sparse Second Order or Descriptor State-Space blocks.
Analyze the time-domain and frequency-domain responses of linearized models. You can compare the responses of multiple models and view system characteristics such as stability margins and settling time.
You can view the state-space equations of your linearized model in the Model Linearizer.
You can assess the accuracy of your linearization results by estimating the frequency response of the nonlinear model and comparing the result with the response of the linearized model.
You can assess the accuracy of your linearization results by comparing the simulated output of the nonlinear model and the linearized model.
To reproduce your interactive linearization results at the command line, you can generate MATLAB® scripts or functions using the Model Linearizer.