Adaptive Dynamical Programming control with combination of off-line and on-line training

This paper studies off-line control and on-line control based on Adaptive Dynamical Programming and proposes an optimal adaptive algorithm with the combination of off-line and on-line training; The method using off-line value iteration algorithm gets off-line opitical controller, then using on-line policy iteration algorithm of Q learning improves the off-line opitical controller. Simulation results show that the proposed approach is effective.