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.
CITATION STYLE
Hassan, S. S., & Sarkka, S. (2023). Fourier-Hermite Dynamic Programming for Optimal Control. IEEE Transactions on Automatic Control, 68(10), 6377–6384. https://doi.org/10.1109/TAC.2023.3234236
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