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Nonlinear Decoupling Control of Induction Motor Based on Parameter Adaptive Identification

机译:基于参数自适应辨识的异步电动机非线性解耦控制

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To solve the shortcomings of large dependence on the parameters and need accurate cancellation the dynamic when using exact linearization method to nonlinear system, this paper introduced the Kalman filter to linear decoupling control to observe the load torque change of induction motor. At the same time, use reactive power model based on MRAS to identification rotor time constant of induction motor. So, can effective tracking the dynamic parameters online of induction motor and achieved settlement the problem of the input-output linearization effected by the variation parameters of motor. Finally, the control system designed in this paper studied by computer simulation. Simulation results show that parameters adaptive identification based on Kalman filter and reactive power model in nonlinear decoupling control of induction motor is feasible and can get satisfactory results.
机译:为了解决对参数的大依赖性的缺点,需要准确取消动态在使用精确的线性化方法到非线性系统时,将卡尔曼滤波器引入线性去耦控制,观察感应电动机的负载扭矩变化。同时,使用基于MRA的无功功率模型来识别电动机的转子时间常数。因此,可以有效地跟踪感应电动机在线的动态参数,并实现了通过电动机变化参数实现的输入输出线性化的问题。最后,通过计算机仿真研究了本文设计的控制系统。仿真结果表明,基于Kalman滤波器的参数自适应识别和感应电动机非线性去耦控制中的无功模型是可行的,可以获得令人满意的结果。

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