Operating Points
Find model operating point from specification (trimming) or simulation time, initialize model at operating point
Anoperating pointof a dynamic system specifies the initial states and root-level input signals of the model at a particular time. You can find operating points using command-line tools, theSteady State Manager, or when linearizing a model using theModel Linearizer. For more information about operating points, seeAbout Operating PointsandCompute Steady-State Operating Points.
Apps
Steady State Manager | Find operating points for金宝appmodels |
Model Linearizer | Linearize金宝appmodels |
Functions
Blocks
Trigger-Based Operating Point Snapshot | Generate operating points at triggered events |
Topics
Steady-State Operating Points
- About Operating Points
An operating point of a dynamic system defines the states and root-level input signals of the model at a specific time. - Compute Steady-State Operating Points
To obtain a steady-state operating point, you can trim your model using numerical optimization techniques or simulate your model until it reaches a steady-state condition. - Handle Blocks with Internal State Representation
The operating point object used for linearization and control design does not include Simulink®blocks with internal state representation, such as内存andTransport Delayblocks. - View and Modify Operating Points
You can view and modify operating point values programmatically at the command line or interactively using the Steady State Manager or Model Linearizer.
Find Operating Points
- Compute Steady-State Operating Points from Specifications
Find a steady-state operating point that meets specifications. You can specify known values or bounds for model states, outputs, and inputs.
- Import and Export Specifications for Operating Point Search
When you modify an operating point specification in the Steady State Manager or Model Linearizer, you can export the specification to the MATLAB®workspace or the Model Linearizer workspace. - Change Operating Point Search Optimization Settings
You can control the accuracy of your operating point search by using different optimization methods. - Initialize Steady-State Operating Point Search Using Simulation Snapshot
If you know the approximate time when the model reaches the neighborhood of a steady-state operating point, you can use simulation to get state values to use as the initial conditions for numerical optimization. - Find Operating Points at Simulation Snapshots
Simulate your model and find an operating point that consists of the state values and model input levels at a specified simulation snapshot time. - Compute Operating Point Snapshots at Triggered Events
You can find an operating point by simulating the model until it is at steady state and taking a simulation snapshot. - Find Steady-State Operating Points for Simscape Models
To find operating points for Simscape™ models, you can trim the models using projection-based trim optimizers, or take simulation snapshots at specified times.
金宝appModel Synchronization
- Synchronize Simulink Model Changes with Operating Point Specifications
Modifying your Simulink model can change, add, or remove states, inputs, or outputs, which changes the operating point. - 模拟仿真软件模型金宝apppecific Operating Point
You can derive your Simulink model initial conditions from your computed operating point.
Custom Trimming
- Compute Operating Points Using Custom Constraints and Objective Functions
Trim Simulink models using additional user-specified constraints and objective functions.
Batch Computation
- Batch Compute Steady-State Operating Points Reusing Generated MATLAB Code
Generate code for trimming your simulink model, and modify the script to batch trim your model. - Batch Compute Steady-State Operating Points for Parameter Variation
Vary model parameters and batch trim your model to find corresponding operating points. - Batch Compute Steady-State Operating Points for Multiple Specifications
Find operating points for multiple operating point specifications using a single model compilation. - Improve Linear Analysis Performance
This example shows how to use thefastRestartForLinearAnalysis
command to speed up multiple calls to compiling functions inSimulink Control Design™such as找到op
andlinearize
.
Code Generation
- Generate MATLAB Code for Operating Point Configuration
You can generate MATLAB code to programmatically reproduce an operating point search result that you obtained interactively.