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"Open-loop-systems": 121,
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"Open-loop-systems": 121,
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"Regulators": 122,
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"Regulators": 122,
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"Three-term-control": 123,
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"Three-term-control": 123,
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"White-noise": 124
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"White-noise": 124,
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"Actuators": 125,
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"Cable-TV": 126,
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"Feedback-control": 127,
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"Optimization": 128,
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"Parametric-statistics": 129,
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"Trajectory": 130,
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"Uncertainty": 131
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},
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},
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}
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200 Library Papers/farzanRobustControlSynthesis2020.md
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200 Library Papers/farzanRobustControlSynthesis2020.md
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---
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readstatus: false
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dateread:
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title: "Robust Control Synthesis and Verification for Wire-Borne Underactuated Brachiating Robots Using Sum-of-Squares Optimization"
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year: 2020
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authors:
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- "Farzan, Siavash"
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- "Hu, Ai-Ping"
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- "Bick, Michael"
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- "Rogers, Jonathan"
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citekey: "farzanRobustControlSynthesis2020"
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pages: 7744-7751
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---
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# Indexing Information
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## DOI
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[10.1109/IROS45743.2020.9341348](https://doi.org/10.1109/IROS45743.2020.9341348)
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## ISBN
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[](https://www.isbnsearch.org/isbn/)
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## Tags:
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#Actuators, #Cable-TV, #Feedback-control, #Optimization, #Parametric-statistics, #Trajectory, #Uncertainty
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>[!Abstract]
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>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.
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>[!note] Markdown Notes
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>None!
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>[!seealso] Related Papers
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>
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# Annotations
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### Imported: 2024-10-16 10:34 am
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How is robust control validation done?.md
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How is robust control validation done?.md
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## Reading Some Papers
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### [[farzanRobustControlSynthesis2020]]
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