vault backup: 2024-10-16 10:37:19

.obsidian/plugins/colored-tags/data.json

@@ -133,7 +133,14 @@
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+    "White-noise": 124,
+    "Actuators": 125,
+    "Cable-TV": 126,
+    "Feedback-control": 127,
+    "Optimization": 128,
+    "Parametric-statistics": 129,
+    "Trajectory": 130,
+    "Uncertainty": 131
   },
   "_version": 3
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200 Library Papers/farzanRobustControlSynthesis2020.md

@@ -0,0 +1,50 @@
+---
+readstatus: false
+dateread:
+title: "Robust Control Synthesis and Verification for Wire-Borne Underactuated Brachiating Robots Using Sum-of-Squares Optimization"
+year: 2020
+authors:
+
+  
+  - "Farzan, Siavash"
+  
+  - "Hu, Ai-Ping"
+  
+  - "Bick, Michael"
+  
+  - "Rogers, Jonathan"
+  
+
+citekey: "farzanRobustControlSynthesis2020"
+
+
+
+
+
+
+
+pages: 7744-7751
+
+---
+# Indexing Information
+## DOI
+[10.1109/IROS45743.2020.9341348](https://doi.org/10.1109/IROS45743.2020.9341348)
+## ISBN
+[](https://www.isbnsearch.org/isbn/)
+## Tags:
+#Actuators, #Cable-TV, #Feedback-control, #Optimization, #Parametric-statistics, #Trajectory, #Uncertainty
+
+>[!Abstract]
+>Control of wire-borne underactuated brachiating robots requires a robust feedback control design that can deal with dynamic uncertainties, actuator constraints and unmeasurable states. In this paper, we develop a robust feedback control for brachiating on flexible cables, building on previous work on optimal trajectory generation and time-varying LQR controller design. We propose a novel simplified model for approximation of the flexible cable dynamics, which enables inclusion of parametric model uncertainties in the system. We then use semidefinite programming (SDP) and sum-of-squares (SOS) optimization to synthesize a time-varying feedback control with formal robustness guarantees to account for model uncertainties and unmeasurable states in the system. Through simulation, hardware experiments and comparison with a time-varying LQR controller, it is shown that the proposed robust controller results in relatively large robust backward reachable sets and is able to reliably track a pre-generated optimal trajectory and achieve the desired brachiating motion in the presence of parametric model uncertainties, actuator limits, and unobservable states.
+
+>[!note] Markdown Notes
+>None!
+
+>[!seealso] Related Papers
+>
+
+# Annotations
+
+### Imported: 2024-10-16 10:34 am
+
+

How is robust control validation done?.md

@@ -0,0 +1,2 @@
+## Reading Some Papers
+### [[farzanRobustControlSynthesis2020]]