To fix parameters of tunable blocks to specified values, see “View and Change Block
Parameterization in Control System Tuner” on page 10-26.- This tuning goal also imposes an implicit stability constraint on the 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.
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 requirement is a hard constraint.
For Transient Goal, f(x) is based upon the relative gap between the tuned response and
the target response:
gap =yt −yreft 2
yref(tr)t 2.
y(t) – yref(t) is the response mismatch, and 1 – yref(tr)(t) is the transient portion of yref
(deviation from steady-state value or trajectory). ⋅ 2 denotes the signal energy (2-
norm). The gap can be understood as the ratio of the root-mean-square (RMS) of the
mismatch to the RMS of the reference transient.
See Also
Related Examples
- “Specify Goals for Interactive Tuning” on page 10-39
- “Manage Tuning Goals” on page 10-177
- “Visualize Tuning Goals” on page 10-187
See Also