Fourier-Hermite Dynamic Programming for Optimal Control

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Date

2023-10-01

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en

Pages

8

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IEEE Transactions on Automatic Control, Volume 68, issue 10, pp. 6377-6384

Abstract

In this article, we propose a novel computational method for solving nonlinear optimal control problems. The method is based on the use of Fourier-Hermite series for approximating the action-value function arising in dynamic programming instead of the conventional Taylor-series expansion used in differential dynamic programming. The coefficients of the Fourier-Hermite series can be numerically computed by using sigma-point methods, which leads to a novel class of sigma-point-based dynamic programming methods. We also prove the quadratic convergence of the method and experimentally test its performance against other methods.

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Keywords

approximate dynamic programming, Convergence, Costs, differential dynamic programming, Dynamic programming, Fourier–Hermite series, Heuristic algorithms, Jacobian matrices, Optimal control, sigma-point dynamic programming, Taylor series, trajectory optimization

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Citation

Hassan, S S & Sarkka, S 2023, ' Fourier-Hermite Dynamic Programming for Optimal Control ', IEEE Transactions on Automatic Control, vol. 68, no. 10, pp. 6377-6384 . https://doi.org/10.1109/TAC.2023.3234236