Robust Control Toolbox

Modeling and Quantifying Plant Uncertainty

With Robust Control Toolbox, you can capture not only the typical, or nominal, behavior of your plant, but also the amount of uncertainty and variability. Plant model uncertainty can result from:

  • Model parameters with approximately known or varying values
  • Neglected or poorly known dynamics, such as high-frequency dynamics
  • Changes in operating conditions
  • Linear approximations of nonlinear behaviors
  • Estimation errors in a model identified from measured data
Plot and corresponding MATLAB code of worst-case gain of a system with an uncertain parameter.
Plot (top) and corresponding MATLAB® code (bottom) of the worst-case gain of a system with an uncertain parameter. Robust Control Toolbox lets you create an uncertain model by adding uncertain elements to nominal plant models and then analyze the effect of uncertainty by calculating the worst-case system performance.

Robust Control Toolbox lets you build detailed uncertain models by combining nominal dynamics with uncertain elements, such as uncertain parameters or neglected dynamics. By quantifying the level of uncertainty in each element, you can capture the overall fidelity and variability of your plant model. You can then analyze how each uncertain element affects performance and identify worst-case combinations of uncertain element values.

Building and Manipulating Uncertain Models
Build uncertain state-space models and analyze the robustness of feedback control systems that have uncertain elements.

Next: Performing Robustness Analysis

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Automatic Tuning of Gain-Scheduled Controllers

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