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ABSTRACT (maximum 200 words)A Galerkin-based family of numerical formulations is presented for solving nonlinear optimal control problems. This dissertation introduces a family of direct methods that calculate optimal trajectories by discretizing the system dynamics using Galerkin numerical techniques and approximate the cost function with Gaussian quadrature. In this numerical approach, the analysis is based on L 2 -norms. An important result in the theoretical foundation is that the feasibility and consistency theorems are proved for problems with continuous and/or piecewise continuous controls. Galerkin methods may be formulated in a number of ways that allow for efficiency and/or improved accuracy while solving a wide range of optimal control problems with a variety of state and control constraints. Numerical formulations using Lagrangian and Legendre test functions are derived. One formulation allows for a weak enforcement of boundary conditions, which imposes end conditions only up to the accuracy of the numerical approximation itself. Additionally, the multi-scale formulation can reduce the dimension of multi-scale optimal control problems, those in which the states and controls evolve on different timescales. Finally, numerical examples are shown to demonstrate the versatile nature of Galerkin optimal control.
SUBJECT TERMS
Solving potential problems, such as those that occur in the analysis of steady-state heat transfer, electrostatics, ideal fluid flow, and groundwater flow, is important in several fields of engineering, science, and applied mathematics. Numerical solution of the relevant governing equations typically involves using techniques such as domain methods (including finite element, finite difference, or finite volume), or boundary element methods (using either real or complex variables). In this paper, the Complex Variable Boundary Element method ("CVBEM") is examined with respect to the use of different types of basis functions in the CVBEM approximation function. Four basis function families are assessed in their solution success in modeling an important benchmark problem in ideal fluid flow; namely, flow around a 90 degree bend. Identical problem domains are used in the examination, and identical degrees of freedom are used in the CVBEM approximation functions. Further, a new computational modeling error is defined and used to compare the results herein; specifically, M = E / N where M is the proposed computational error measure, E is the maximum difference (in absolute value) between approximation and boundary condition value, and N is the number of degrees of freedom used in the approximation.
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