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

机译:基于DOB的双轴系统的广义预测交叉耦合位置控制

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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,通过双轴系统统一模型的概念引入了广义预测交叉耦合控制(GPCCC)策略。 GPCCC控制设计由两个过程组成。首先,根据多步预测,滚动优化和反馈校正的已知轨迹,应用于两个永磁同步电动机(PMSM)的统一模型,以提高双轴控制的准确性,应用于两个永磁同步电动机(PMSM)的统一模型。然后,轮廓误差采用可以是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。然而,它反映了GPCCC控制设计不考虑干扰和不确定性的影响。因此,通过将干扰观察者(DOB)嵌入输出预测过程来提出复合GPCCC方法以估计集体扰动。仿真结果表明,用于跟踪双轴系统中提出的方法的性能的高精度和稳健性。

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