Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

2% uncertainty, but the tuned RPT design can tolerate up to 11%. Tuning the PT
design also does better at this requirement, allowing just under 9.2% variation in the
uncertainty parameters. At this relaxed requirement. there is no longer a regime
where only tuned PT works. The RPT designs can both compensate for uncertainty
and provide a fair amount of tuning authority. Relaxing the requirement further,
above 350µm for example, greatly increases the benefits of tuning the RPT design.
At these requirement levels tuning the PT design can accommodate 11% variation in
uncertainty parameters, but tuning the RPT design extends the range out to 20%.
It is clear from the comparison of Figures 4-7 and 3-12 that tuning the hardware
has a significant impact on the design space. At a given requirement, a larger variation
in the uncertainty parameters can be tolerated if the hardware is tuned to improve
the system performance. The addition of a tuning step to the overall design process
allows a greater level of risk for systems with aggressive performance goals. In the
next section, practical methods for tuning hardware, when the realized values of the
uncertainty parameters are not exlicitly known, are explored.
4.2 Tuning in Practical Application
The results presented in the previous section demonstrate that hardware tuning is
effective in improving system performance and extends the limits of RPT and PT
design. The studies are conducted on models in which the uncertain parameters
are known, since systems under worst-case uncertainty are considered. In practical
application, however, the engineer does not have the advantage of full knowledge of
the uncertain parameters. Even though the hardware is built and these parameters
are no longer random, their values can rarely be measured directly. For example,
in the case of Young’s Modulus, it is very difficult, if not impossible, to measure
the exact value of this parameter even with access to the hardware. Despite this
difficulty there is information available that can indirectly lead to the identification
of the uncertainty parameters and successful tuning of the hardware. In this section,
the practical problem of tuning the hardware when only performance data is available
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