We investigate the use of an approximation method for obtaining near-optimal solutions to a kind of nonlinear continuous-time(CT) system. The approach derived from the Galerkin approximation is used to solve the gener...We investigate the use of an approximation method for obtaining near-optimal solutions to a kind of nonlinear continuous-time(CT) system. The approach derived from the Galerkin approximation is used to solve the generalized Hamilton-Jacobi-Bellman(GHJB) equations. The Galerkin approximation with Legendre polynomials(GALP) for GHJB equations has not been applied to nonlinear CT systems. The proposed GALP method solves the GHJB equations in CT systems on some well-defined region of attraction. The integrals that need to be computed are much fewer due to the orthogonal properties of Legendre polynomials, which is a significant advantage of this approach. The stabilization and convergence properties with regard to the iterative variable have been proved.Numerical examples show that the update control laws converge to the optimal control for nonlinear CT systems.展开更多
基金supported by the China Postdoctoral Science Foundation(No.2013M531842)the Natural Science Foundation of Guangdong Province,China(No.2015A030313497)the Science and Technology Program of Guangzhou,China(No.2014KP000039)
文摘We investigate the use of an approximation method for obtaining near-optimal solutions to a kind of nonlinear continuous-time(CT) system. The approach derived from the Galerkin approximation is used to solve the generalized Hamilton-Jacobi-Bellman(GHJB) equations. The Galerkin approximation with Legendre polynomials(GALP) for GHJB equations has not been applied to nonlinear CT systems. The proposed GALP method solves the GHJB equations in CT systems on some well-defined region of attraction. The integrals that need to be computed are much fewer due to the orthogonal properties of Legendre polynomials, which is a significant advantage of this approach. The stabilization and convergence properties with regard to the iterative variable have been proved.Numerical examples show that the update control laws converge to the optimal control for nonlinear CT systems.
