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Synchronous Reluctance Motor Speed Tracking Using a Modified Second-Order Sliding Mode Control Method

机译:改进的二阶滑模控制方法同步磁阻电动机速度跟踪

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摘要

A modified second-order sliding mode control (MSOSMC) combined with radial basis function (RBF) network estimator is developed and proposed to achieve accurate speed tracking performance for synchronous reluctance motor (SynRM). The dynamic model of SynRM system has the properties of parameter variations, external disturbance, and nonlinear friction force. The MSOSMC method that utilizes continuous control input is applied to reduce the chattering phenomenon. Also, this method utilizes two sliding surfaces to solve the problem of system uncertainty and reduce motor power consumption. The RBF network is developed in MSOSMC scheme to estimate the lumped uncertainty in an on-line fashion. The proposed MSOSMC method uses the system error and control input as the convergence criteria. The adaptation scheme adjusts the parameter vectors based on the Lyapunov theorem approach, so that the asymptotic stability of the developed motor system can be guaranteed. Experimental results show that the MSOSMC structure achieves the better tracking performances in terms of root-mean-square error compared with the traditional SOSMC method under different speed tracking conditions.
机译:提出并结合径向基函数(RBF)网络估计器的改进的二阶滑模控制(MSOSMC),以实现同步磁阻电机(SynRM)的精确速度跟踪性能。 SynRM系统的动力学模型具有参数变化,外部干扰和非线性摩擦力的特性。采用了利用连续控制输入的MSOSMC方法来减少抖动现象。而且,该方法利用两个滑动表面来解决系统不确定性的问题并减少电动机功耗。 RBF网络是按照MSOSMC方案开发的,以在线方式估计集总的不确定性。提出的MSOSMC方法使用系统误差和控制输入作为收敛标准。该自适应方案基于李雅普诺夫定理方法来调整参数矢量,从而可以保证所开发的电机系统的渐近稳定性。实验结果表明,在不同的速度跟踪条件下,与传统的SOSMC方法相比,MSOSMC结构在均方根误差方面具有更好的跟踪性能。

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