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4 Qualifying Exam/2 Writing/1. QE Goals and Outcomes.md
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@ -41,7 +41,7 @@ These generated plants can be used to verify robustness of controller implementa
<mark style="background: #FFF3A3A6;">The goal of this research is to use a generative diffusion model to create unstructured perturbations of a nominal plant.</mark> <mark style="background: #FFB86CA6;">In the real world</mark>, there is always a perturbation between the dynamics of the physical process and the mathematical model. Stability and performance of the controller suffer when this difference is large, <mark style="background: #FFB8EBA6;"><mark style="background: #FFB86CA6;">but knowing that it is never zero, understanding how much performance is affected by the perturbation is important to know</mark></mark>. <mark style="background: #FFB86CA6;">Robust control answers this problem for mathematical models of plants.</mark> <mark style="background: #FFB86CA6;">We can know precisely how much a model of a controller will be affected by a perturbation, and we can define a set of allowable perturbations that fit within our engineering specifications.
</mark>
<mark style="background: #ABF7F7A6;">A problem arises when we try to verify the robustness on an actual modern controller.</mark> In the actual implementation of control laws, there are several intermediate layers between the hardware, firmware, and software that can introduce mistakes. <mark style="background: #FFB8EBA6;">Unlike the model controller, we cannot easily verify that this controller has the same performance over the set of perturbed plants.</mark> The modern controller can only be tested with single elements from the set of plants. Because of this, we suggest using a diffusion generative model to generate elements from this set to validate implementations of controllers to be robust.
<mark style="background: #ABF7F7A6;">A problem arises when we try to verify the robustness on an actual modern controller.</mark> In the actual implementation of control laws, there are several intermediate layers between the hardware, firmware, and software that can introduce mistakes. <mark style="background: #FFB8EBA6;">Unlike the model controller, we cannot easily verify that this controller has the same performance over the set of perturbed plants.</mark> <mark style="background: #FFB86CA6;">The modern controller</mark> can only be tested with single elements from the set of plants. Because of this, we suggest using a diffusion generative model to generate elements from this set to validate implementations of controllers to be robust.
If this research is successful, this diffusion model will accomplish three main tasks:
1. It will approximate a set of controllable plants by generating a large number of perturbed examples