A fuzzy neural recurrent multi-model for systems identification and control

The paper proposed to apply a fuzzy-neural recurrent multi-model for systems identification and states estimation of complex nonlinear plants. The parameters of the local recurrent neural network models are used for a local indirect adaptive trajectory tracking control systems design. The designed local control laws are coordinated by a fuzzy rule based control system. The applicability of the proposed intelligent control system is confirmed by simulation results.