enforce a tuning requirement for a subset of models in an array, select Only Models.
Then, enter the array indices of the models for which the goal is enforced. For
example, suppose you want to apply the tuning goal to the second, third, and fourth
models in a model array. To restrict enforcement of the requirement, enter 2:4 in the
Only Models text box.For more information about tuning for multiple models, see “Robust Tuning
Approaches” (Robust Control Toolbox).Algorithms
When you tune a control system, the software converts each tuning goal into a normalized
scalar value f(x). Here, x is the vector of free (tunable) parameters in the control system.
The software then adjusts the parameter values to minimize f(x) or to drive f(x) below 1 if
the tuning goal is a hard constraint.
For Weighted Gain Goal, f(x) is given by:
fx = WLHs,x WR∞.H(s,x) is the closed-loop transfer function between the specified inputs and outputs,
evaluated with parameter values x. Here, ⋅ ∞ denotes the H∞ norm (see
getPeakGain).
This tuning goal also imposes an implicit stability constraint on the weighted closed-loop
transfer function between the specified inputs to outputs, evaluated with loops opened at
the specified loop-opening locations. The dynamics affected by this implicit constraint are
the stabilized dynamics for this tuning goal. The Minimum decay rate and Maximum
natural frequency tuning options control the lower and upper bounds on these implicitly
constrained dynamics. If the optimization fails to meet the default bounds, or if the
default bounds conflict with other requirements, on the Tuning tab, use Tuning Options
to change the defaults.
See Also
Related Examples
- “Specify Goals for Interactive Tuning” on page 10-39
See Also