Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

Chapter 4
Dynamic Tuning
Robust Performance Tailoring (RPT) optimization results in a design that is tailored
to be robust to parametric uncertainty across a large range of values. Robustness is
achieved by sacrificing nominal performance, so that the nominal, and consequently
worst-case, performance predictions increase with the level of uncertainty. Therefore,
although the RPT design is insensitive to uncertainty, it may not meet agressive
performance requirements. The trade between robustness and nominal performance
places high-performance and high-uncertainty systems outside of the RPT design
regime.
In the following chapter, dynamic tuning is explored as a method of extending the
capabilities of PT and RPT design, by exploiting the additional information available
from hardware testing. First, a formal definition of dynamic tuning is provided,
and the optimization problem is formulated. Tuning parameters are identified in
the SCI development model and SQP and SA optimization techniques are employed
to tune the worst-case uncertainty realizations of the PT and RPT designs. The
tuned designs are considered in the context of the design regimes introduced in the
previous chapter, and it is shown that tuning increases the level of uncertainty that
can be tolerated at a given performance requirement. Then, a spectrum of tuning
methods for practical application, in which the value of the uncertainty parameters
are unknown, ranging from pure hardware tuning to model-based techniques are
discussed. A hybrid method that uses isoperformance techniques to facilitate model
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