vault backup: 2024-10-17 10:50:13

200 Library Papers/stevebruntonControlBootcampLimitations2017.md

@@ -0,0 +1,53 @@
+---
+readstatus: false
+dateread:
+title: "Control Bootcamp:  Limitations on Robustness"
+year: 2017
+authors:
+
+  
+  - "Steve Brunton"
+  
+
+citekey: "stevebruntonControlBootcampLimitations2017"
+
+
+
+
+
+
+
+---
+# Indexing Information
+## DOI
+[](https://doi.org/)
+## ISBN
+[](https://www.isbnsearch.org/isbn/)
+## Tags:
+
+
+>[!Abstract]
+>This video describes some of the fundamental limitations of robustness, including time delays and right-half plane zeros.  
+
+Code available at: faculty.washington.edu/sbrunton/control_bootcamp_code.zip
+
+These lectures follow Chapters 1 & 3 from:
+
+Machine learning control, by Duriez, Brunton, & Noack
+https://www.amazon.com/Machine-Learni...
+
+Chapters available at: http://faculty.washington.edu/sbrunto...
+
+This video was produced at the University of Washington
+
+>[!note] Markdown Notes
+>None!
+
+>[!seealso] Related Papers
+>
+
+# Annotations
+
+### Imported: 2024-10-17 10:42 am
+
+

200 Library Papers/stevebruntonControlBootcampSensitivity2017.md

@@ -0,0 +1,53 @@
+---
+readstatus: false
+dateread:
+title: "Control Bootcamp:  Sensitivity and Robustness"
+year: 2017
+authors:
+
+  
+  - "Steve Brunton"
+  
+
+citekey: "stevebruntonControlBootcampSensitivity2017"
+
+
+
+
+
+
+
+---
+# Indexing Information
+## DOI
+[](https://doi.org/)
+## ISBN
+[](https://www.isbnsearch.org/isbn/)
+## Tags:
+
+
+>[!Abstract]
+>Here we show that peaks in the sensitivity function result in a lack of robustness. 
+
+Code available at: faculty.washington.edu/sbrunton/control_bootcamp_code.zip
+
+These lectures follow Chapters 1 & 3 from:
+
+Machine learning control, by Duriez, Brunton, & Noack
+https://www.amazon.com/Machine-Learni...
+
+Chapters available at: http://faculty.washington.edu/sbrunto...
+
+This video was produced at the University of Washington
+
+>[!note] Markdown Notes
+>None!
+
+>[!seealso] Related Papers
+>
+
+# Annotations
+
+### Imported: 2024-10-17 10:43 am
+
+

201 Metadata/My Library.bib

@@ -11066,6 +11066,30 @@ Subject\_term: Careers, Politics, Policy},
   abstract = {This video motivates robust control with the famous 1978 paper by John Doyle, titled "Guaranteed Margins for LQG Regulators"... Abstract:  There are none.   Code available at: faculty.washington.edu/sbrunton/control\_bootcamp\_code.zip These lectures follow Chapters 1 \& 3 from: Machine learning control, by Duriez, Brunton, \& Noack https://www.amazon.com/Machine-Learni... Chapters available at: http://faculty.washington.edu/sbrunto... This video was produced at the University of Washington}
 }
 
+@video{stevebruntonControlBootcampLimitations2017,
+  entrysubtype = {video},
+  title = {Control {{Bootcamp}}:  {{Limitations}} on {{Robustness}}},
+  shorttitle = {Control {{Bootcamp}}},
+  editor = {{Steve Brunton}},
+  editortype = {director},
+  date = {2017-03-08},
+  url = {https://www.youtube.com/watch?v=ReAmUJMb1d8},
+  urldate = {2024-10-17},
+  abstract = {This video describes some of the fundamental limitations of robustness, including time delays and right-half plane zeros.   Code available at: faculty.washington.edu/sbrunton/control\_bootcamp\_code.zip These lectures follow Chapters 1 \& 3 from: Machine learning control, by Duriez, Brunton, \& Noack https://www.amazon.com/Machine-Learni... Chapters available at: http://faculty.washington.edu/sbrunto... This video was produced at the University of Washington}
+}
+
+@video{stevebruntonControlBootcampSensitivity2017,
+  entrysubtype = {video},
+  title = {Control {{Bootcamp}}:  {{Sensitivity}} and {{Robustness}}},
+  shorttitle = {Control {{Bootcamp}}},
+  editor = {{Steve Brunton}},
+  editortype = {director},
+  date = {2017-03-08},
+  url = {https://www.youtube.com/watch?v=7lzH-HnUFZg},
+  urldate = {2024-10-17},
+  abstract = {Here we show that peaks in the sensitivity function result in a lack of robustness.  Code available at: faculty.washington.edu/sbrunton/control\_bootcamp\_code.zip These lectures follow Chapters 1 \& 3 from: Machine learning control, by Duriez, Brunton, \& Noack https://www.amazon.com/Machine-Learni... Chapters available at: http://faculty.washington.edu/sbrunto... This video was produced at the University of Washington}
+}
+
 @article{stiasnyPhysicsInformedNeuralNetworks2023,
   title = {Physics-{{Informed Neural Networks}} for {{Time-Domain Simulations}}: {{Accuracy}}, {{Computational Cost}}, and {{Flexibility}}},
   shorttitle = {Physics-{{Informed Neural Networks}} for {{Time-Domain Simulations}}},

4 Qualifying Exam/3 Notes/Feedback Control Theory.md

@@ -99,3 +99,11 @@ W_2 is basically a transfer function that will always be greater in magnitude th
 >>[!important] Robust Performance
 >>$$ |||W_1 S | + |W_2 T| ||_\infty < 1 $$
 >>![[Pasted image 20241015172708.png]]
+
+Something really helpful to think about came to mind as a result of watching a Steve Brunton video[^1]. Think about the way that loop gain works:
+$$ y = \frac{L}{1+L} r $$
+If at a certain frequency $\omega$, L approaches -1, big problems happen. What this means is that the denominator in the above equation gets really small, which means the gain from r to y actually gets really big. If it IS -1, immediate undefined blow up. 
+
+This is where robustness comes from. The distance between L and -1 for all frequencies is what robustness is. Less distance, less room for plant perturbation that could make you unstable. More distance, safer response. 
+
+[^1]: [[stevebruntonControlBootcampSensitivity2017]]