Application of RBF Neural Network to Simplify the Potential Based Optimization

A policy iteration approach to optimal control problems for a class of nonlinear stochastic dynamic system is introduced. Some parameters and nonlinearities of the system are not required to be known a-priori. An optimality equation is developed based on performance potential. The potential can be estimated by a sample path, and then it is approximated by RBF neural network. As a result, an on-line algorithm is proposed by using a sample path of the given control system.