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DSP-based synchronous control of dual linear motors via sugeno type fuzzy neural network compensator

机译:sugeno型模糊神经网络补偿器的双线性电动机基于DSP的同步控制

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A digital signal processor (DSP)-based complementary sliding mode control (CSMC) with Sugeno type fuzzy neural network (SFNN) compensator is proposed in this study for the synchronous control of a dual linear motors servo system installed in a gantry position stage. The dual linear motors servo system comprises two parallel permanent magnet linear synchronous motors (PMLSMs). The dynamics of the single-axis motion system with a lumped uncertainty which contains parameter variations, external disturbances and nonlinear friction force is briefly introduced first. Then, a CSMC is designed to guarantee the precision position tracking requirement in single-axis control for the dual linear motors. Moreover, to enhance the robustness to uncertainties and to eliminate the synchronous error of dual linear motors, the CSMC with a SFNN compensator is proposed where the SFNN compensator is designed mainly to compensate the synchronous error. Finally, some experimental results are illustrated to show the validity of the proposed control approach.
机译:本研究提出了一种基于数字信号处理器(DSP)的带有Sugeno型模糊神经网络(SFNN)补偿器的互补滑模控制(CSMC),用于安装在龙门位置台上的双线性电机伺服系统的同步控制。双线性电动机伺服系统包括两个并联的永磁线性同步电动机(PMLSM)。首先简要介绍具有集中不确定性的单轴运动系统的动力学,该不确定性包含参数变化,外部干扰和非线性摩擦力。然后,设计了CSMC以确保双线性电机在单轴控制中的精确位置跟踪要求。此外,为了增强对不确定性的鲁棒性并消除双线性电动机的同步误差,提出了一种带有SFNN补偿器的CSMC,其中SFNN补偿器主要用于补偿同步误差。最后,通过一些实验结果说明了所提出的控制方法的有效性。

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