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Robust Hierarchical Control With Connected Layers.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	Robust Hierarchical Control With Connected Layers./
Author:	Schweidel, Katherine.
Description:	1 online resource (101 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
Contained By:	Dissertations Abstracts International85-03B.
Subject:	Mechanical engineering. -
Online resource:	click for full text (PQDT)
ISBN:	9798380368773

Robust Hierarchical Control With Connected Layers.
Schweidel, Katherine.

Robust Hierarchical Control With Connected Layers. - 1 online resource (101 pages)

Source: Dissertations Abstracts International, Volume: 85-03, Section: B.

Thesis (Ph.D.)--University of California, Berkeley, 2023.

Includes bibliographical references

Complex systems, such as autonomous vehicles and missile guidance systems, use hierarchical control schemes where each control layer employs a different system model. This approach enhances computational efficiency because using a simpler model in the higher-level control layer reduces computation times, enabling real-time control strategies. This dissertation presents a framework in which a lower-fidelity planning model is employed for online planning, and a tracking controller, synthesized offline, keeps the tracking error between the high-fidelity ("tracking") model and the planning model within a bounded set. To ensure safety, the error that arises from the different models in each control layer is rigorously accounted for through augmentation of the planner safety constraints with the tracking error bound.Accommodating more sources of real-world uncertainty enhances the safety and usefulness of the control scheme. We next describe a robust extension which utilizes integral quadratic constraints to accommodate input uncertainties such as unknown delays or unmodeled actuator dynamics in the tracking model. Finally, through a case study of shared vehicle control between a human driver and a supervisory autonomous system in longitudinal driving scenarios, we present a novel method called Driver-in-the-Loop Contingency MPC that leverages simplified dynamics to compute invariant sets that guarantee safety with respect to other vehicles. This contribution can be viewed as adding robustness to other agents in the planning layer.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380368773Subjects--Topical Terms:

557493
Mechanical engineering.
Subjects--Index Terms:

TrackingIndex Terms--Genre/Form:

554714
Electronic books.

Robust Hierarchical Control With Connected Layers.
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500 $a Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
500 $a Advisor: Arcak, Murat.
502 $a Thesis (Ph.D.)--University of California, Berkeley, 2023.
504 $a Includes bibliographical references
520 $a Complex systems, such as autonomous vehicles and missile guidance systems, use hierarchical control schemes where each control layer employs a different system model. This approach enhances computational efficiency because using a simpler model in the higher-level control layer reduces computation times, enabling real-time control strategies. This dissertation presents a framework in which a lower-fidelity planning model is employed for online planning, and a tracking controller, synthesized offline, keeps the tracking error between the high-fidelity ("tracking") model and the planning model within a bounded set. To ensure safety, the error that arises from the different models in each control layer is rigorously accounted for through augmentation of the planner safety constraints with the tracking error bound.Accommodating more sources of real-world uncertainty enhances the safety and usefulness of the control scheme. We next describe a robust extension which utilizes integral quadratic constraints to accommodate input uncertainties such as unknown delays or unmodeled actuator dynamics in the tracking model. Finally, through a case study of shared vehicle control between a human driver and a supervisory autonomous system in longitudinal driving scenarios, we present a novel method called Driver-in-the-Loop Contingency MPC that leverages simplified dynamics to compute invariant sets that guarantee safety with respect to other vehicles. This contribution can be viewed as adding robustness to other agents in the planning layer.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Mechanical engineering. $3 557493
650 4 $a Computer engineering. $3 569006
650 4 $a Automotive engineering. $3 1104081
653 $a Tracking
653 $a Complex systems
653 $a Autonomous vehicles
653 $a Hierarchical control
653 $a Augmentation
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710 2 $a University of California, Berkeley. $b Mechanical Engineering. $3 845449
773 0 $t Dissertations Abstracts International $g 85-03B.
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