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Convex optimization based planning and control methods for space-robotic systems

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Title
Convex optimization based planning and control methods for space-robotic systems
Name (type = personal)
NamePart (type = family)
Misra
NamePart (type = given)
Gaurav
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1989-
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Gaurav Misra
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author
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Bai
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Xiaoli
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Xiaoli Bai
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Advisory Committee
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chair
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Benaroya
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Haym
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Haym Benaroya
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internal member
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Zou
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Qingze
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Qingze Zou
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Advisory Committee
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internal member
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Lu
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Ping
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Ping Lu
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Advisory Committee
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outside member
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Rutgers University
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degree grantor
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School of Graduate Studies
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school
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Text
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theses
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2019
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2019-10
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2019
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English
Abstract (type = abstract)
Space-robotic systems are arguably the most promising technologies available currently for on-orbit satellite operations including docking, berthing, and repair, which have been demonstrated in typically manned and semi-autonomous missions. Another important application of space-robotic systems is space debris mitigation. Space debris are uncooperative space objects (i.e. without any internal actuation) including defunct satellites and spent rocket stages, all of which pose tremendous risk to current operational space assets. Autonomous robotic capture, control, and stabilization of such objects are becoming critical. However, space-robotic operations in proximity of such uncooperative object is challenging with large uncertainties.

As a result, optimality, robustness, and tractability constitute some of the desirable properties for any planning and control algorithm used for spacecraft guidance, control, and robotic operations.
Through the development of fast interior point methods for solving convex optimization problems with globally optimality, convex programming methods have been proposed and experimentally validated for real-time guidance and control of space systems. However, most current developments have explored solving locally optimal solutions to highly non-linear and constrained optimal control problems in real-time. The issues of robustness, tractability, and global optimality are still open problems.

To this end, this thesis investigates robust and optimal planning and control schemes for space-robotics that leverage convex programming. Primarily, four theoretical advances have been made: 1.) Exact reformulation for control of deterministic, nonlinear robotic systems as a convex program; 2.) Sequential, emph{iteratively feasible} convex relaxations leading to locally optimal solutions using difference of convex functions programming; 3.) Hierarchy of convex relaxations of systems formulated exactly or approximated with polynomial dynamics with global optimality certificates and guaranteed convergence; and 4.) Robust controller synthesis for nonlinear polynomial systems using polynomial optimization in the framework of nonlinear disturbance observers for both matched and mismatched uncertainties.

For applications, the thesis solves four challenging problems for trajectory planning and control during spacecraft proximity operation. First, quadratic programming based trajectory planning methods are formulated for free-floating space robots. Leveraging tools in analytical mechanics and differential geometry, a novel quadratic programming based trajectory planning scheme is developed for task-constrained end-effector motion which minimizes the base attitude disturbance, in addition to obstacle avoidance for both the unactuated base and manipulator. Second, the orbital station-keeping of spacecraft in the framework of the circular restricted three-body problem is solved using polynomial optimization in a receding horizon setting. Third, robust stabilization and tracking of spacecraft attitude motion in the presence of parametric uncertainties and external disturbances is explored in the framework of convex optimization based nonlinear disturbance observer synthesis. And fourth, an iteratively feasible convex programming based approach is proposed for solving optimal spacecraft guidance problems with non-convex constraints such as obstacle avoidance.
Subject (authority = RUETD)
Topic
Mechanical and Aerospace Engineering
Subject (authority = LCSH)
Topic
Space robotics
Subject (authority = LCSH)
Topic
Convex programming
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Title
Rutgers University Electronic Theses and Dissertations
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ETD_10151
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application/pdf
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1 online resource (xv, 143 pages) : illustrations
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
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School of Graduate Studies Electronic Theses and Dissertations
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rucore10001600001
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Identifier (type = doi)
doi:10.7282/t3-72ym-c533
Genre (authority = ExL-Esploro)
ETD doctoral
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The author owns the copyright to this work.
RightsHolder (type = personal)
Name
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Misra
GivenName
Gaurav
Role
Copyright Holder
RightsEvent
Type
Permission or license
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2019-08-05 02:55:48
AssociatedEntity
Name
Gaurav Misra
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Copyright holder
Affiliation
Rutgers University. School of Graduate Studies
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I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
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Copyright protected
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Open
Reason
Permission or license
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2019-08-04T23:47:17
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