A new method based on least-squares support vector regression for solving optimal control problems

In this paper, a new application of the Least Squares Support Vector Regression (LS-SVR) with Legendre basis functions as mapping functions to a higher dimensional future space is considered for solving optimal control problems.At the final stage of LS-SVR, an optimization problem is formulated and solved using Maple optimization packages.The accuracy of the method are illustrated through numerical examples, including nonlinear optimal control problems.The results demonstrate that the proposed method is capable of solving optimal control problems with high accuracy.