Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT

eigenvalue derivatives are used to obtain RMS gradients with respect to design
variables for use in gradient-based optimizations.
• Application of the robust design framework to a simple model of a structurally
connected interferometer. Realistic control (tailing and tuning) and noise (un-
certainty) factors are identified.
• Application of dynamic tailoring and tuning optimizations to a simple model of
a structurally connected interferometer. Three tailoring methods are compared
in terms of ability to meet performance requirements given model uncertainty.
In addition, three existing robust cost functions are applied and compared in
terms of the robustness of the resulting design.
• Application of dynamic tailoring and tuning optimizations to a high-fidelity
model of a structurally-connected TPF interferometer. NASTRAN and MAT-
LAB are integrated to perform a heuristic multi-disciplinary design optimiza-
tion.
7.3 Future Work
The recommendations for future work focus on four main areas: uncertainty model-
ing, RPTT methodology, isoperformance tuning and application. An itemized list of
specific recommendations are provided below:
• Uncertainty Modeling
– Consider sources of uncertainty other than parametric errors. Explore the
ability of the RPTT framework to compensate for discretization errors and
unmodelled effects.
– Consider additional forms of uncertainty models. In particular, examine
the effect of RPTT when probabilistic uncertainty models are used in place
of bounded.
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