A kind of nonlinear adaptive inverse control systems based on fuzzy neural networks

A model reference adaptive inverse control system (MRAICS) based on fuzzy neural networks (FNN), which comprises adaptive disturbance canceller and feedback compensation, is presented in This work. The feedback compensation can counteract the MRAIC system´s direct current zero-frequency drift. The adaptive disturbance canceler can best erase disturbances. Nonlinear filters based on FNN are used in the nonlinear plant modeling, the design of the controller and adaptive disturbance canceller. The nonlinear filters can deal with nonlinear system and result in fast convergence. Simulation result shows that the approach is effective.