Convergence Analysis of Adaptive Critic Based Optimal Control
This document has been relocated to http://scholarsmine.mst.edu/mec_aereng_facwork/3414
There were 10 downloads as of 28 Jun 2016.
Adaptive critic based neural networks have been found to be powerful tools in solving various optimal control problems. The adaptive critic approach consists of two neural networks which output the control values and the Lagrangian multipliers associated with optimal control. These networks are trained successively and when the outputs of the two networks are mutually consistent and satisfy the differential constraints, the controller network output produces optimal control. In this paper, we analyze the mechanics of convergence of the network solutions. We establish the necessary conditions for the network solutions to converge and show that the converged solution is optimal.