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DOB-Based Generalized Predictive Cross-Coupling Position Control for Biaxial System

机译:基于DOB的双轴系统广义预测交叉耦合位置控制

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摘要

In order to optimize the control performance of the biaxial systems, the generalized predictive cross coupling control (GPCCC) strategy is introduced with the concept of a unified model in biaxial systems. GPCCC control design consists of two processes. First, generalized prediction algorithm is applied to the unified model of the two permanent magnet synchronous motors (PMSM), according to the known trajectory of multi-step prediction, rolling optimization and feedback correction to improve the accuracy of biaxial control. Then, the contour error adopts cross-coupling structure which can be the feedback quantity, as the extra correction of generalized predictive control structure. However, it reflects that the GPCCC control design does not consider the influence of disturbances and uncertainties. Therefore, a composite GPCCC method is proposed by embedding the disturbance observer (DOB) into the output prediction process to estimate the lumped disturbances. The simulation results demonstrate the high accuracy and the robustness for tracking performance of the proposed method in the biaxial system.
机译:为了优化双轴系统的控制性能,在双轴系统中引入了统一模型的概念,引入了广义预测交叉耦合控制(GPCCC)策略。 GPCCC控制设计包括两个过程。首先,根据已知的多步预测,滚动优化和反馈校正轨迹,将广义预测算法应用于两个永磁同步电动机(PMSM)的统一模型,以提高双轴控制的精度。然后,轮廓误差采用可以作为反馈量的交叉耦合结构,作为广义预测控制结构的额外校正。但是,这反映出GPCCC控制设计没有考虑干扰和不确定性的影响。因此,通过将干扰观测器(DOB)嵌入到输出预测过程中来估计集总干扰,提出了一种复合GPCCC方法。仿真结果表明,该方法在双轴系统中具有很高的跟踪精度和鲁棒性。

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