Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

equired by the optimization or stochastic search algorithm involves a new test setup
and data acquisition. In contrast, optimizations performed on the model are much
cheaper requiring only computational effort. In this section some model-only tuning
schemes are considered.
Nominal Model Tuning
A very simple approach to model-only tuning is to tune the nominal model for im-
proved performance and apply this tuning configuration to the hardware. If the shape
of the performance space with respect to the tuning parameters is similar for the nom-
inal model and the hardware, then a tuning configuration that improves the nominal
model performance may also improve the hardware performance. If the hardware
performance is only slightly above the requirement or the degree of uncertainty is
low then this improvement may be enough to bring the system within specification.
The optimization formulation is very similar to that of the tuning formulation in
Equation 4.2 with �p0 replacing the actual uncertainty values, ˜p:
min f (˜x, �y, �p0)
�y
(4.11)
s.t. �g (˜x, �y) ≤ 0
This technique is referred to as nominal model tuning throughout the rest of this
chapter.
Robust Tuning with Anti-optimization
A second model-only tuning method is to apply the robust performance tailoring ideas
to the tuning problem. The anti-optimization method is chosen as the cost function
to obtain a conservatively robust design. The formulation is the nearly the same as
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