danesabo/Obsidian
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

vault backup: 2024-11-25 15:25:57

Browse Source
This commit is contained in:
Dane Sabo 2024-11-25 15:25:57 -05:00
parent 536cb4cb8e
commit 0725c44c61
2 changed files with 14 additions and 14 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
.obsidian/plugins/obsidian-style-settings/data.json vendored
View File

@ -4,7 +4,7 @@
"anuppuccin-theme-settings-extended@@anp-theme-ext-light": true,
"anuppuccin-theme-settings-extended@@anp-theme-ext-dark": true,
"anuppuccin-theme-settings-extended@@catppuccin-theme-extended": "ctp-notion-light",
"anuppuccin-theme-settings-extended@@catppuccin-theme-dark-extended": "ctp-generic-dark",
"anuppuccin-theme-settings-extended@@catppuccin-theme-dark-extended": "ctp-gruvbox-dark",
"anuppuccin-theme-settings@@anuppuccin-theme-dark": "ctp-frappe",
"anuppuccin-theme-settings@@anp-custom-checkboxes": true,
"anuppuccin-theme-settings@@anp-speech-bubble": true,

26
4 Qualifying Exam/4 Presentation/Outline.md
View File

@ -14,7 +14,7 @@ Ideas taken from https://services.anu.edu.au/files/development_opportunity/Resea
- As a result, we need to reverify robustness on built controllers
- This exists for structured perturbations. We
# Gap In The Literature
### **Slide 1: Robust Control Foundations**
## **Slide 1: Robust Control Foundations**
**Assertion:** Robust control ensures stability despite system discrepancies.
**Evidence:**
@ -26,7 +26,7 @@ Ideas taken from https://services.anu.edu.au/files/development_opportunity/Resea
---
### **Slide 2: Structured vs. Unstructured Perturbations**
## **Slide 2: Structured vs. Unstructured Perturbations**
**Assertion:** Robust control addresses structured and unstructured perturbations differently.
**Evidence:**
@ -38,7 +38,7 @@ Ideas taken from https://services.anu.edu.au/files/development_opportunity/Resea
---
### **Slide 3: Disk-Based Unstructured Uncertainty**
## **Slide 3: Disk-Based Unstructured Uncertainty**
**Assertion:** Disk-based perturbation quantifies unstructured uncertainties.
**Evidence:**
@ -55,7 +55,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 4: Current Limitations in Robust Control**
## **Slide 4: Current Limitations in Robust Control**
**Assertion:** Current methods lack discrete examples of unstructured perturbations.
**Evidence:**
@ -66,7 +66,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 5: Diffusion Models as a Solution**
## **Slide 5: Diffusion Models as a Solution**
**Assertion:** Diffusion models can generate unstructured perturbations.
**Evidence:**
@ -79,7 +79,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 6: Parallels Between Diffusion Models and This Project**
## **Slide 6: Parallels Between Diffusion Models and This Project**
**Assertion:** Diffusion models address sparse perturbation generation in engineering.
**Evidence:**
@ -90,7 +90,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
# Goals and Outcomes
# Research Methodology
### **Slide 1: Research Motivation**
## **Slide 1: Research Motivation**
**Assertion:** Current methods for generating unstructured perturbations are limited in flexibility and generalizability.
@ -104,7 +104,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 2: Diffusion Model Features**
## **Slide 2: Diffusion Model Features**
**Assertion:** Frequency response data forms the foundation for feature creation in diffusion models.
@ -118,7 +118,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 3: Creating Frequency Features**
## **Slide 3: Creating Frequency Features**
**Assertion:** Discretizing the frequency response enables scalable feature sets.
@ -133,7 +133,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 4: Training the Diffusion Model**
## **Slide 4: Training the Diffusion Model**
**Assertion:** Diffusion models learn unstructured perturbations through iterative noise transformation.
@ -148,7 +148,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 5: Generating New Perturbations**
## **Slide 5: Generating New Perturbations**
**Assertion:** The trained diffusion model generates diverse and flexible perturbations.
@ -163,7 +163,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 6: Ensuring Valid Perturbations**
## **Slide 6: Ensuring Valid Perturbations**
**Assertion:** Generated perturbations must meet robust control requirements.
@ -178,7 +178,7 @@ _(Include a visual of how $\Delta$ affects $P$)_
---
### **Slide 7: Advantages of Diffusion Models**
## **Slide 7: Advantages of Diffusion Models**
**Assertion:** Diffusion models provide a novel solution for generating unstructured perturbations.