Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

timization (Equation 4.2) to the model at the worst-case uncertainty vertex. The
resulting optimal tuning parameters and tuned performances for the three designs
are listed in Table 5.3. In all cases, the tuning mass is concentrated in one arm of the
interferometer. The RPTT design is tuned on the positive-x arm while the PT and
RPT designs are tuned by adding mass to the negative-x arm. This mirror effect is
simply due to the choice of worst-case uncertainty vertex. Since the model is perfectly
symmetric there are two vertices that result in the same worst-case performance.
The tuned performance values indicate that the RPTT design can achieve the
best performance through a combination of tailoring and tuning. Consider, for ex-
ample, a performance requirement of 240µm, shown with a solid horizontal line in
Figure 5-1. Nominal performance is indicated by circles and tuned performance by
triangles. The top of the solid error bars is the worst-case untuned performance, and
the dashed error bar denotes the worst-case tuned performance. The PT design meets
Performance [µm]
1400
1200
1000
800
600
400
200
0
Requirement
Nominal
Worst−Case Tuned
PT RPT RPTT
Figure 5-1: Nominal, worst-case and tuned performance for PT, RPT and RPTT
designs. Nominal and tuned performances shown with circles and triangles, respectively,
and worst-case performance indicated by error bars. The solid black horizontal
line indicates a performance requirement of 240 µm.
this requirement nominally with a performance value of 100.58µm, but is far above
160