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Robust Hierarchical Control With Con...

Schweidel, Katherine.

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Robust Hierarchical Control With Connected Layers.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Robust Hierarchical Control With Connected Layers./
Author:	Schweidel, Katherine.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2023,
Description:	101 p.
Notes:	Source: Dissertations Abstracts International, Volume: 85-03, Section: B.
Contained By:	Dissertations Abstracts International85-03B.
Subject:	Mechanical engineering. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30567415
ISBN:	9798380368773

Robust Hierarchical Control With Connected Layers.
Schweidel, Katherine.

Robust Hierarchical Control With Connected Layers. - Ann Arbor : ProQuest Dissertations & Theses, 2023 - 101 p.

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

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

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.

ISBN: 9798380368773Subjects--Topical Terms:

649730
Mechanical engineering.
Subjects--Index Terms:

Tracking

Robust Hierarchical Control With Connected Layers.
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245 1 0 $a Robust Hierarchical Control With Connected Layers.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2023
300 $a 101 p.
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.
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.
590 $a School code: 0028.
650 4 $a Mechanical engineering. $3 649730
650 4 $a Computer engineering. $3 621879
650 4 $a Automotive engineering. $3 2181195
653 $a Tracking
653 $a Complex systems
653 $a Autonomous vehicles
653 $a Hierarchical control
653 $a Augmentation
690 $a 0548
690 $a 0464
690 $a 0540
710 2 $a University of California, Berkeley. $b Mechanical Engineering. $3 1043692
773 0 $t Dissertations Abstracts International $g 85-03B.
790 $a 0028
791 $a Ph.D.
792 $a 2023
793 $a English
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