vault backup: 2024-10-02 10:53:51

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Dane Sabo 2024-10-02 10:53:51 -04:00
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@ -91,4 +91,6 @@ If this research is successful, this diffusion model will accomplish three main
Perturbing a nominal plant to establish robustness is not a new technique. Robust control can find the set of plants with which a controller remains performant. Finding this set is a well understood problem, and can be straightforward. An engineer can use this set of plants to guarantee how robust a nominal controller is to perturbation. But, engineer cannot use this set to make guarantees about a implemented controller. Implementation of control laws requires lowering the abstraction level from the model of a controller to a computer program. Robustness of this controller implementation can be suggested by analysis of the model, but can be verified through experimentation. Perturbing a nominal plant to establish robustness is not a new technique. Robust control can find the set of plants with which a controller remains performant. Finding this set is a well understood problem, and can be straightforward. An engineer can use this set of plants to guarantee how robust a nominal controller is to perturbation. But, engineer cannot use this set to make guarantees about a implemented controller. Implementation of control laws requires lowering the abstraction level from the model of a controller to a computer program. Robustness of this controller implementation can be suggested by analysis of the model, but can be verified through experimentation.
Experimentally verifying robustness for implementations of controllers requires elements to be extracted from the set. There are two main ways this has been done: structured and unstructured perturbations. Structured perturbations are created manually: an engineer attributes probability distributions to certain system parameters to include a margin of error. These distributions are sampled to create the perturbation. Unstructured perturbations are trickier to generate, because the perturbation form is not defined. Experimentally verifying robustness for implementations of controllers requires elements to be extracted from the set. There are two main ways this has been done: structured and unstructured perturbations. Structured perturbations are created manually: an engineer attributes probability distributions to certain system parameters to include a margin of error. These distributions are sampled to create the perturbation. Unstructured perturbations are trickier to generate, because the perturbation form is not defined. It can be difficult to find perturbations that are 'random' while remaining within the allowable set.
This research will utilize a diffusion model to make generation of unstructured perturbations easier.