Dynamic adaptive learning algorithm based on two-fuzzy neural-networks

A dynamic adaptive learning algorithm based on two fuzzy neural-networks for the control of a partially unknown nonlinear dynamic system is developed in this paper. The proposed fuzzy neural-network controller is composed of a computation controller and a learning controller. The computation controller and a learning controller will control collaboratively for partially unknown nonlinear dynamic system. Formally, the stability of the control system and convergence of the fuzzy neural-network have been proved. The proposed algorithm based on two fuzzy neural-networks can avoid the time-consuming trial-and-error tuning procedure for determining structure and parameters. The simulation experiment shows that the proposed method is feasible, valid and rational.