Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

Performance [µm]
1400
1200
1000
800
600
400
200
Nominal
Worst−Case
Standard Deviation
0
0 0.2 0.4 0.6 0.8 1
Performance Weight, α
Figure 3-5: Nominal performance (o), worst-case (�) performance and standard deviation
(*) for vertex statistical robustness (VSR) RPT designs vs nominal performance
weighting, α.
The squares on the plot represent the worst-case performance, or the performance
at the worst-case uncertainty vertex. As α increases, and the weight on robustness
decreases, the worst-case performance increases nonlinearly. There is significant jump
in the worst-case performance at α =0.8, and as the weighting approaches α =1.0
the curves plateau to the performance of the PT design.
3.3.2 Objective function comparisons
In the previous section the different implementations of optimization with the three
RPT cost functions are compared for computational efficiency and performance. The
combination of SA and SQP algorithms consistently achieves a lower cost value in
less time than MC SQP. In this section the SQP RPT designs are compared against
each other and the PT design for robustness.
The nominal and worst-case performance values for the PT and RPT designs
are plotted in Figure 3-6(a), and the values are listed in the accompanying table
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