Robust control of induction motor speed regulation system based on fuzzy neural network generalized inverse

According to the multivariable nonlinear and coupling of the Induction Motor Speed Regulation System, a strategy of robust control based on fuzzy neural network (FNN) generalized inverse system (GIS) is adopted. Being properly designed, a FNN is used to construct the generalized inversion of the induction motor´s speed regulation system and a pseudo-linear system with open-loop stability is obtained after connecting them. A robust controller is designed based on two-degree of freedom internal model control (IMC) by which the rotator speed can be controlled accurately. Experiment results show that this pseudo-linear system has open-loop stability and good static and dynamic performance and the strong robustness to load torque disturbance and parametric perturbation, un-modeled dynamics et al. can be achieved by using the designed controller.