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Plant Specification

Specify plant model, input and output signal types, scale factors

Model predictive controllers use linear models to control both linear and nonlinear plants that run within a local operating range. Plants with complex characteristics such as long time delays, higher-order dynamics, or strong interactions are particularly well-suited for model predictive control. To create a plant model, you can directly specify a linear model, linearize a Simulink® model, or identify a linear model using measured data. When creating a plant model for use in model predictive control, it is important to specify the input and output signal types and scale factors. For more information, see MPC Signal Types and Specify Scale Factors.

Functions

setmpcsignalsSet signal types in LTI plant model
getnameRetrieve I/O signal names from MPC plant model
setnameSet I/O signal names in MPC plant model

Topics

Model and Signals

  • MPC Signal Types
    Plant inputs are independent variables that affect the plant, and plant outputs are dependent variables that you want to control or monitor.
  • MPC Prediction Models
    Model predictive controllers use plant, disturbance, and noise models for prediction and state estimation.
  • Specify Scale Factors
    When designing an MPC controller, it is good practice to define scale factors for each plant input and output, especially when variables have large differences in magnitude.

Obtain LTI Models