基于模糊神经网络逆系统的五自由度无轴承永磁同步电机自抗扰控制

为了实现五自由度无轴承永磁同步电机的高性能控制,提出一种基于Takagi-Sugeno(T-S)型模糊神经网络逆系统的自抗扰控制方法.首先,基于五自由度无轴承永磁同步电机(5-DOF BPMSM)的结构及运行原理,建立五自由度无轴承永磁同步电机的数学模型,并对数学模型进行了可逆性分析.其次,利用T-S型模糊神经网络的非...

Active disturbance rejection control for 5-degree-of-freedom bearingless permanent magnet synchronous motor based on inverse system using the fuzzy neural network

To realize the high-performance control of the 5-degree-of-freedom bearingless permanent magnet synchronous motor(5-DOF BPMSM),an active disturbance rejection control method based on the inverse system using the Takagi-Sugeno(T-S)fuzzy neural network is proposed.Firstly,based on the structure and the operational principle of the 5-DOF BPMSM,the mathematical model was deduced,and the reversibility of the mathematical model was analyzed.Secondly,the T-S fuzzy neural network with excellent nonlinear approximation ability was applied to construct the inverse system of the 5-DOF BPMSM,and the nonlinear original system was decoupled into six independent pseudo-linear subsystems by series connection with the constructed inverse system.Thirdly,considering the characteristics of the pseudo-linear subsystems,the active disturbance rejection control theory was used to design extra controllers to ensure the stability of the pseudo-linear subsystems.Finally,the comparative simulations and experiments between the proposed method and the traditional PID control method based on the inverse system were carried out.The results indicate that the proposed method has better decoupling performance,higher control accuracy and stronger robustness.