感应电机调速系统模糊神经网络逆鲁棒控制

Robust Control of Induction Motor Speed Regulation System Based on Fuzzy Neural Networks Inversion

以多变量、非线性、强耦合的感应电机调速系统为研究对象,采用模糊神经网络逆鲁棒控制策略,通过模糊神经网络加积分器来构造感应电机调速系统的动态逆系统,将二者串联重构成伪线性复合系统,基于内模控制,根据复合系统的特性设计鲁棒控制器,实现了感应电机转速的高精度鲁棒控制。仿真和实验结果表明系统具有优良的静态及动态性能,对负载扰动、参数摄动和未建模动态等具有很强的鲁棒性。

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） inverse system was adopted,A FNN and one integrator were used to reconstruct the dynamic inversion of the induction motor＇s speed regulation system and a pseudo-linear system was obtained after connecting them,A robust controller was designed based on internal mode control by which the rotator speed can be controlled accurately.Simulation and experiment results show that the good static and dynamic performance and the strong robustness to load torque disturbance and parametric perturbation,unmodeled dynamics can be achieved by using the proposed method.