Improved Dynamic Modeling and Robust Control of Autonomous Underwater Vehicles

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dc.contributor.authorGibson, Scott Brianen
dc.contributor.committeechairStilwell, Daniel J.en
dc.contributor.committeememberWoolsey, Craig A.en
dc.contributor.committeememberMacKenzie, Allen B.en
dc.contributor.committeememberBrizzolara, Stefanoen
dc.contributor.committeememberTokekar, Pratapen
dc.contributor.departmentElectrical Engineeringen
dc.date.accessioned2018-08-02T08:00:18Zen
dc.date.available2018-08-02T08:00:18Zen
dc.date.issued2018-08-01en
dc.description.abstractIn this dissertation, we seek to improve the dynamic modeling and control of autonomous underwater vehicles (AUVs). We address nonlinear hydrodynamic modeling, simplifying modeling assumptions, and robust control for AUVs. In the literature, various hydrodynamic models exist with varying model complexity and with no universally accepted model. We compare various hydrodynamic models traditionally employed to predict the motion of AUVs by estimating model coefficients using least-squares and adaptive identifier techniques. Additionally, we derive several dynamic models for an AUV employing varying sets of simplifying assumptions. We experimentally assess the efficacy of invoking typical assumptions to simplify the equations of motion. For robust control design, we develop a procedure for designing robust attitude controllers based on loop-shaping ideas. We specifically address the challenge of adjusting the desired actuator bandwidth in a loop-shaping design framework. Finally, we present a novel receding horizon H-infinity control algorithm to improve the control of autonomous vehicle systems working in high-disturbance environments, employing a Markov jump linear system framework to model the stochastic and non-stationary disturbances experienced by the vehicle. Our main results include a new Bounded Real Lemma for stability analysis and an output feedback H-infinity control synthesis algorithm. This work uses numerical simulations and extensive field trials of autonomous underwater vehicles to identify and verify dynamic models and to validate control algorithms developed herein.en
dc.description.abstractgeneralIn this dissertation, we seek to improve the dynamic modeling and control of autonomous underwater vehicles (AUVs). We compare different models employed to predict the motion of AUVs, and we derive several dynamic models for an AUV employing varying sets of simplifying assumptions. We experimentally assess the efficacy of invoking typical assumptions to simplify the equations of motion. For robust control design, we develop a procedure for designing robust controllers that do not produce excessive fin movements. Finally, we present a novel robust control algorithm to improve the control of autonomous vehicle systems working in high-disturbance environments. This work uses numerical simulations and extensive field trials of autonomous underwater vehicles to identify and verify dynamic models and to validate control algorithms developed herein.en
dc.description.degreePh. D.en
dc.format.mediumETDen
dc.identifier.othervt_gsexam:16585en
dc.identifier.urihttp://hdl.handle.net/10919/84468en
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectautonomous vehiclesen
dc.subjectdynamicsen
dc.subjectparameter estimationen
dc.subjectH-infinity controlen
dc.subjecttime-inhomogeneous Markov jump linear systemsen
dc.titleImproved Dynamic Modeling and Robust Control of Autonomous Underwater Vehiclesen
dc.typeDissertationen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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