1,903 research outputs found

    Investigation of optimization of attitude control systems, volume i

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    Optimization of attitude control systems by development of mathematical model and computer program for space vehicle simulatio

    The max-plus finite element method for solving deterministic optimal control problems: basic properties and convergence analysis

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    We introduce a max-plus analogue of the Petrov-Galerkin finite element method to solve finite horizon deterministic optimal control problems. The method relies on a max-plus variational formulation. We show that the error in the sup norm can be bounded from the difference between the value function and its projections on max-plus and min-plus semimodules, when the max-plus analogue of the stiffness matrix is exactly known. In general, the stiffness matrix must be approximated: this requires approximating the operation of the Lax-Oleinik semigroup on finite elements. We consider two approximations relying on the Hamiltonian. We derive a convergence result, in arbitrary dimension, showing that for a class of problems, the error estimate is of order δ+Δx(δ)−1\delta+\Delta x(\delta)^{-1} or δ+Δx(δ)−1\sqrt{\delta}+\Delta x(\delta)^{-1}, depending on the choice of the approximation, where δ\delta and Δx\Delta x are respectively the time and space discretization steps. We compare our method with another max-plus based discretization method previously introduced by Fleming and McEneaney. We give numerical examples in dimension 1 and 2.Comment: 31 pages, 11 figure

    An adaptive POD approximation method for the control of advection-diffusion equations

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    We present an algorithm for the approximation of a finite horizon optimal control problem for advection-diffusion equations. The method is based on the coupling between an adaptive POD representation of the solution and a Dynamic Programming approximation scheme for the corresponding evolutive Hamilton-Jacobi equation. We discuss several features regarding the adaptivity of the method, the role of error estimate indicators to choose a time subdivision of the problem and the computation of the basis functions. Some test problems are presented to illustrate the method.Comment: 17 pages, 18 figure
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