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 ...
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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 dynamicprogramming instead of the conventional Taylor-series expansion used in differential dynamicprogramming. 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 dynamicprogramming methods. We also prove the quadratic convergence of the method and experimentally test its performance against other methods.
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