Neural Networks Solving Free and Fixed Final Time Optimal Control Problems

Abstract

In this paper, the neural network based optimal control synthesis is presented for solving free and fixed final time optimal control problems with the control and state constraints. The optimal control problem is transcribed into a nonlinear programming problem, which is implemented with the adaptive critic neural network. The proposed simulation methods are illustrated by the optimal control problem of photosynthetic production and the nitrogen transformation cycle model. The results show that the adaptive critic based systematic approach is promising in obtaining free and fixed final time optimal control with the control and state constraints.