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Current-Sensorless Finite-Set Model Predictive Control for

机译:传感器的无传感器有限集模型预测控制

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A typical finite-set model predictive control (FS-MPC) scheme for LC-filtered voltage source inverters (VSIs) requires measurements of capacitor voltage and inductor current as well as load currentmeasurement or estimation, which increases the system complexity and cost. To reduce the number of sensors in typical FS-MPC, this paper proposes a new current-sensorless FS-MPC scheme for LC-filtered VSIs. First, based on the inner relationship of the predictivematrices, the predictive model is exactly simplified with the capacitor voltage and its current as the state variables, making it suitable for current-sensorless control. Then, to eliminate the current sensors for cost reduction and reliability enhancement, the dynamic model is reconstructed and an easily implemented capacitor current estimator is designed, which can achieve a comparable performance with typical FS-MPC scheme. Considering the inevitable control delay in digital implementation, the delay compensation is inherently obtained by using the proposed estimator. In addition, the proposed control scheme is flexible to various cost functions and can also reduce the computational cost. The feasibility of the presented control scheme under load variations and model mismatches are verified by the comparative simulation and experimental results with typical FS-MPC.
机译:用于LC滤波电压源逆变器(VSI)的典型有限集模型预测控制(FS-MPC)方案需要测量电容器电压和电感器电流以及负载电流或进行估计,这会增加系统的复杂性和成本。为了减少典型FS-MPC中的传感器数量,本文针对LC滤波VSI提出了一种新的无电流传感器FS-MPC方案。首先,基于预测矩阵的内部关系,以电容器电压及其电流作为状态变量来精确简化预测模型,使其适合于无电流传感器控制。然后,为了消除电流传感器以降低成本和提高可靠性,重建了动态模型,并设计了易于实现的电容器电流估计器,该电容器可以实现与典型FS-MPC方案相当的性能。考虑到数字实现中不可避免的控制延迟,延迟补偿是通过使用所提出的估计器固有地获得的。另外,所提出的控制方案对于各种成本函数是灵活的,并且还可以降低计算成本。通过比较仿真和典型FS-MPC的实验结果,验证了所提出的控制方案在负载变化和模型不匹配下的可行性。

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