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Uncertainty analysis of power systems using collocation

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dc.contributor.advisor Franz Hover. en_US Taylor, Joshua Adam en_US
dc.contributor.other Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US 2009-06-30T16:33:17Z 2009-06-30T16:33:17Z 2008 en_US 2008 en_US
dc.description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2008. en_US
dc.description Includes bibliographical references (p. 93-97). en_US
dc.description.abstract The next-generation all-electric ship represents a class of design and control problems in which the system is too large to approach analytically, and even with many conventional computational techniques. Additionally, numerous environmental interactions and inaccurate system model information make uncertainty a necessary consideration. Characterizing systems under uncertainty is essentially a problem of representing the system as a function over a random space. This can be accomplished by sampling the function, where in the case of the electric ship a "sample" is a simulation with uncertain parameters set according to the location of the sample. For systems on the scale of the electric ship, simulation is expensive, so we seek an accurate representation of the system from a minimal number of simulations. To this end, collocation is employed to compute statistical moments, from which sensitivity can be inferred, and to construct surrogate models with which interpolation can be used to propagate PDF's. These techniques are applied to three large-scale electric ship models. The conventional formulation for the sparse grid, a collocation algorithm, is modified to yield improved performance. Theoretical bounds and computational examples are given to support the modification. A dimension-adaptive collocation algorithm is implemented in an unscented Kalman filter, and improvement over extended Kalman and unscented filters is seen in two examples. en_US
dc.description.statementofresponsibility by Joshua Adam Taylor. en_US
dc.format.extent 97 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri en_US
dc.subject Mechanical Engineering. en_US
dc.title Uncertainty analysis of power systems using collocation en_US
dc.type Thesis en_US S.M. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Mechanical Engineering. en_US
dc.identifier.oclc 320449964 en_US

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