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中文摘要：
针对无轴承异步电机非线性、多变量、强耦合的特点,提出一种基于神经网络α阶逆系统方法的非线性内模控制策略.将用动态神经网络逼近的无轴承异步电机α阶逆模型与原系统复合,将非线性的无轴承异步电机原系统解耦成转子径向位移、转速和转子磁链四个独立的伪线性子系统.为了保证系统的鲁棒性,对伪线性系统引入内模控制,仿真和实验研究验证了所提控制方法的有效性.
英文摘要：
The bearingless induction motor is a nonlinear, multi-variable and strongly coupled system. For this system, a novel internal model control strategy based on neural network αth-order inverse system theory is proposed in this paper to realize the decoupling control. By cascading the αth-order inverse model approximated by the dynamic neural network with the original system, the nonlinear bearingless induction motor system is decoupled into four independent pseudo-linear subsystems, that is, two radial displacement subsystems, a speed subsystem and a rotor flux subsystem. Then, the internal model control method is introduced to the four pseudo-linear subsystems to ensure the robustness and antijamming ability of the closed-loop system. The effectiveness and superiority of the proposed strategy are demonstrated by simulation and experiment.
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