Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT
Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT Chapter 5 Robust Performance Tailoring with Tuning - SSL - MIT
to solve the performance tailoring problem on the development model. The results are compared to assess efficiency and performance of the optimization techniques, and the optimal design is analyzed. In Chapter 3, parametric uncertainties in the model are considered, and it is shown that the performance tailored design is very sensitive to changes in the uncertain parameters. Therefore, the problem of space-based interferometer design is posed in a robust design framework. A selection of robust design approaches including multiple model, anti-optimization and statistical robustness are compared and contrasted on the SCI development model. The resulting RPT design is compared to the PT design at both the nominal and worst-case uncertainty values. Specific design regimes are identified by considering the worst-case performance of the PT and RPT designs as the level of uncertainty increases. It is shown that, although robust design significantly increases the amount of uncertainty that can be tolerated, a limit is reached for systems that are highly uncertain yet require a level of performance at which these techniques are no longer adequate. In Chapter 4, the concept of dynamic tuning is introduced as a way to extend the performance of the PT and RPT designs. Tuning is defined as changes made to the hardware once it is built to bring the system within performance requirements. Pos- sible tuning parameters and appropriate selection criteria are discussed. A spectrum of tuning methodologies are presented ranging from model updating to experimental hardware optimization. Methods are compared through application to the develop- ment model, and a hybrid methodology using isoperformance for model updating is developed. Tuning techniques are applied to hardware simulations of the development model to improve performance under parametric uncertainty. The focus of Chapter 5 is the development of the RPTT design methodology. It is a formal synthesis of the tailoring and tuning techniques detailed in the previous chap- ters in which the design is tailored to plan for future tuing adjustments on hardware. Tailoring for tuning is demonstrated on the development model, and a comparison of PT, RPT and RPTT techniques is presented over a range of uncertainty levels to illustrate the benefits of formally combining tailoring and tuning. It is shown that 36
the level of tolerable uncertainty is extended past that of robust design techniques alone. In Chapter Six, the PT, RPT and RPTT methodologies are applied to a high- fidelity integrated model of a structurally-connected interferometer architecture for TPF. Appropriate tuning, tailoring and uncertainty parameters are identified, and the design methodologies are demonstrated. Trends similar to those exhibited by the development model are observed. Limitations of the optimizations algorithms are identified and recommendations for increasing computational efficiency are made. Finally, in Chapter 7 the thesis contributions are highlighted and recommenda- tions for future work are enumerated. 37
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- Page 41 and 42: ometer (SCI). In the following sect
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to solve the performance tailoring problem on the development model. The results<br />
are compared to assess efficiency and performance of the optimization techniques,<br />
and the optimal design is analyzed.<br />
In <strong>Chapter</strong> 3, parametric uncertainties in the model are considered, and it is shown<br />
that the performance tailored design is very sensitive to changes in the uncertain<br />
parameters. Therefore, the problem of space-based interferometer design is posed in<br />
a robust design framework. A selection of robust design approaches including multiple<br />
model, anti-optimization and statistical robustness are compared and contrasted on<br />
the SCI development model. The resulting RPT design is compared to the PT design<br />
at both the nominal and worst-case uncertainty values. Specific design regimes are<br />
identified by considering the worst-case performance of the PT and RPT designs as the<br />
level of uncertainty increases. It is shown that, although robust design significantly<br />
increases the amount of uncertainty that can be tolerated, a limit is reached for<br />
systems that are highly uncertain yet require a level of performance at which these<br />
techniques are no longer adequate.<br />
In <strong>Chapter</strong> 4, the concept of dynamic tuning is introduced as a way to extend the<br />
performance of the PT and RPT designs. <strong>Tuning</strong> is defined as changes made to the<br />
hardware once it is built to bring the system <strong>with</strong>in performance requirements. Pos-<br />
sible tuning parameters and appropriate selection criteria are discussed. A spectrum<br />
of tuning methodologies are presented ranging from model updating to experimental<br />
hardware optimization. Methods are compared through application to the develop-<br />
ment model, and a hybrid methodology using isoperformance for model updating is<br />
developed. <strong>Tuning</strong> techniques are applied to hardware simulations of the development<br />
model to improve performance under parametric uncertainty.<br />
The focus of <strong>Chapter</strong> 5 is the development of the RPTT design methodology. It is<br />
a formal synthesis of the tailoring and tuning techniques detailed in the previous chap-<br />
ters in which the design is tailored to plan for future tuing adjustments on hardware.<br />
<strong>Tailoring</strong> for tuning is demonstrated on the development model, and a comparison<br />
of PT, RPT and RPTT techniques is presented over a range of uncertainty levels to<br />
illustrate the benefits of formally combining tailoring and tuning. It is shown that<br />
36
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