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• W3204193585 abstract "Two of the main challenges in optimal control are solving problems with state-dependent running costs and developing efficient numerical solvers that are computationally tractable in high dimension. In this paper, we provide analytical solutions to certain optimal control problems whose running cost depends on the state variable and with constraints on the control. We also provide Lax-Oleinik-type representation formulas for the corresponding Hamilton-Jacobi partial differential equations with state-dependent Hamiltonians. Additionally, we present an efficient, grid-free numerical solver based on our representation formulas, which is shown to scale linearly with the state dimension, and thus, to overcome the curse of dimensionality. Using existing optimization methods and the min-plus technique, we extend our numerical solvers to address more general classes of convex and nonconvex initial costs. We demonstrate the capabilities of our numerical solvers using implementations on a central processing unit (CPU) and a field-programmable gate array (FPGA). In several cases, our FPGA implementation obtains over a 10 times speedup compared to the CPU, which demonstrates the promising performance boosts FPGAs can achieve. Our numerical results show that our solvers have the potential to serve as a building block for solving broader classes of high-dimensional optimal control problems in real-time." @default.
• W3204193585 created "2021-10-11" @default.
• W3204193585 creator A5031706939 @default.
• W3204193585 creator A5065114974 @default.
• W3204193585 creator A5076546851 @default.
• W3204193585 date "2021-09-30" @default.
• W3204193585 modified "2023-09-24" @default.
• W3204193585 title "Lax-Oleinik-type formulas and efficient algorithms for certain high-dimensional optimal control problems" @default.
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• W3204193585 doi "https://doi.org/10.48550/arxiv.2109.14849" @default.
• W3204193585 hasPublicationYear "2021" @default.
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